final report honours project: through-the-wall imaging...

Final Report

Honours Project: Through-the-Wall Imaging Radar

Student: Supervisors:

Thang Bui (1173888) Prof. Douglas Gray

Partner: Mr. Richard DrakeJoseph Rabig (1162140)

October 21, 2011

Executive Summary

A through-wall imaging radar could have many applications where it is important to view

a visually and physically obstructed area. Typical applications for such radar are search and

rescue, police and military operations. The desired purpose of a through-the-wall system is to

estimate or detect the inner content and structure of a room behind the wall, or layout of a

building. Further actions, such as sending personnel inside the obscured area can be followed

accordingly once the result is extracted.

This project was conducted to investigate the feasibility of constructing a Synthetic Aperture

Radar using a Vector Network Analyser as the waveform generator and a pair of horn antennas

being moved to form a Synthetic Aperture, in order to image the objects behind the wall.

The arrangement of the antennas could follow bistatic or pseudo-monostatic configuration. For

each movement of the antennas, the forward gain of the environment was measured. MATLAB

programs were used for focusing implementation to generate the images of the region using

recorded data.

2-D image of the region of interest behind a wall has been successfully generated. The

pseudo-monostatic configuration results in better cross range resolution compared to bistatic

case. Experiments were conducted for various wall materials (pin-up board, plaster wall and

office wall) and the results prove the feasibility of through the wall imaging application using

a Synthetic Aperture Radar. The designed radar system is simple and of low cost, which can

be used for research application. The outcome of this project serves as a foundation for the

implementation of a more complex through-wall radar system.

Acknowledgements

To Prof. Doug Gray and Mr. Richard Drake for your advice and guidance for the project.

Your support and knowledge are invaluable for the completion of this project.

To Joseph Rabig for being part of the project. It has been a pleasure working with you.

To staffs of EEE School for your generous help and support, from administrative works

or part acquirement to construction.

To Prof. Bevan Bates from DSTO for providing the loan of a pair of horn antennas.

Contents

List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

List of Codes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

1 Introduction 1

1.1 Aims . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.2 Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.3 Background and Significance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.4 Project overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.5 Document structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2 Synthetic Aperture Radar Imaging 4

2.1 Power Consideration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2.2 Range Resolution and Pulse Compression . . . . . . . . . . . . . . . . . . . . . . 5

2.3 Cross-range Resolution and Radar Configurations . . . . . . . . . . . . . . . . . 7

2.4 Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.4.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.4.2 Calibration using Electronic Calibration Kit . . . . . . . . . . . . . . . . 11

2.4.3 Calibration using Linear Regression . . . . . . . . . . . . . . . . . . . . . 12

2.5 Focusing Technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

2.5.1 Focusing Delay Formulation . . . . . . . . . . . . . . . . . . . . . . . . . 14

2.5.1.1 When there is no wall . . . . . . . . . . . . . . . . . . . . . . . 14

2.5.1.2 When there is a wall . . . . . . . . . . . . . . . . . . . . . . . . 15

2.5.2 Imaging implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

2.5.2.1 Time domain implementation . . . . . . . . . . . . . . . . . . . 17

2.5.2.2 Frequency domain implementation . . . . . . . . . . . . . . . . 19

2.6 Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

3 Experimental Set-up and Initial Experiments 21

3.1 Equipments and Experimental Environment . . . . . . . . . . . . . . . . . . . . 21

3.2 Experiment with Patch Antenna . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

i

3.3 Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

4 Imaging Experiments and Results 26

4.1 Experimental Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

4.2 Imaging of objects without wall . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

4.2.1 1-object imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

4.2.2 2-object imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

4.3 Imaging result for a pin-up board . . . . . . . . . . . . . . . . . . . . . . . . . . 31

4.4 Imaging result for a constructed wall . . . . . . . . . . . . . . . . . . . . . . . . 33

4.4.1 Set up . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

4.4.2 Empty room . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

4.4.3 No wall . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

4.4.4 One plaster board . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

4.4.5 Two plaster boards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

4.5 Imaging result for a real office wall . . . . . . . . . . . . . . . . . . . . . . . . . 41

4.6 Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

5 Project Management 45

5.1 Work Plan and Schedule Revisit . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

5.2 Risk Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

5.2.1 Risk occurred . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

5.2.1.1 Delay in material procurement and construction . . . . . . . . . 47

5.2.1.2 Subversion blackout . . . . . . . . . . . . . . . . . . . . . . . . 47

5.2.1.3 Anechoic chamber and VNA unavailable . . . . . . . . . . . . . 48

5.2.1.4 Lack of technical knowledge . . . . . . . . . . . . . . . . . . . . 48

5.3 Budget review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

6 Conclusion 49

6.1 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

6.2 Project Outcomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

Bibliography 52

A MATLAB Code 53

ii

List of Figures

2.1 Stepped-frequency signal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2.2 Sample reflection measurement from VNA . . . . . . . . . . . . . . . . . . . . . 7

2.3 Monostatic configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

2.4 Bistatic configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.5 Distance from Horn 1 to Horn 2 via pixel Pi for monostatic and bistatic cases . 9

2.6 1D experiment set up . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.7 Impulse responses for different antenna separations . . . . . . . . . . . . . . . . 10

2.8 Relative response between two separations . . . . . . . . . . . . . . . . . . . . . 11

2.9 Desired vs. Actual delays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

2.10 Electronic Calibration kit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

2.11 Cable response and calibration result using ECal module . . . . . . . . . . . . . 12

2.12 Linear Regression for calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

2.13 Sample experimental result for linear regression . . . . . . . . . . . . . . . . . . 13

2.14 Calibration technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

2.15 Pre- and post-calibration impulse response . . . . . . . . . . . . . . . . . . . . . 14

2.16 2-D imaging system configuration . . . . . . . . . . . . . . . . . . . . . . . . . . 15

2.17 2-D imaging system configuration with wall . . . . . . . . . . . . . . . . . . . . 16

2.18 2-D imaging system configuration with wall . . . . . . . . . . . . . . . . . . . . 16

2.19 Imaging technique in time domain . . . . . . . . . . . . . . . . . . . . . . . . . . 18

2.20 Imaging technique in frequency domain . . . . . . . . . . . . . . . . . . . . . . . 19

3.1 Synthetic aperture radar and Agilent PNA (VNA) . . . . . . . . . . . . . . . . . 21

3.2 ECal module and DSTO horn antennas . . . . . . . . . . . . . . . . . . . . . . . 22

3.3 Patch antenna and R&S ZVL VNA . . . . . . . . . . . . . . . . . . . . . . . . . 22

3.4 Forward voltage gain for a cross-polarised patch antenna . . . . . . . . . . . . . 23

3.5 Impulse response for a cross-polarised patch antenna . . . . . . . . . . . . . . . 23

3.6 Simulation result for time domain implementation . . . . . . . . . . . . . . . . . 25

3.7 Simulation result for frequency domain implementation . . . . . . . . . . . . . . 25

4.1 Image of one object in the chamber . . . . . . . . . . . . . . . . . . . . . . . . . 28

4.2 Down-range and cross-range profiles at peak location . . . . . . . . . . . . . . . 28

4.3 Image of two objects at same range in the chamber . . . . . . . . . . . . . . . . 29

iii

4.4 Down range profiles at peak location for image of 2 objects . . . . . . . . . . . . 30

4.5 Cross range profile at peak location for image of 2 objects . . . . . . . . . . . . 30

4.6 Imaging result of two objects at different ranges . . . . . . . . . . . . . . . . . . 30

4.7 Result for pin-up board – Pseudo-monostatic . . . . . . . . . . . . . . . . . . . . 32

4.8 Result for pin-up board – Bistatic . . . . . . . . . . . . . . . . . . . . . . . . . . 32

4.9 Experimental set up for constructed wall . . . . . . . . . . . . . . . . . . . . . . 33

4.10 Imaging result for an empty controlled room . . . . . . . . . . . . . . . . . . . . 34

4.11 Imaging result for controlled environment without wall . . . . . . . . . . . . . . 34

4.12 Imaging profiles for pseudo-monostatic configuration . . . . . . . . . . . . . . . 35

4.13 Imaging profiles for bistatic configuration . . . . . . . . . . . . . . . . . . . . . . 35

4.14 Imaging result for one plaster board wall . . . . . . . . . . . . . . . . . . . . . . 36



4.17 Imaging result for two plaster boards wall . . . . . . . . . . . . . . . . . . . . . 39



4.20 Experimental set-up for a real office wall . . . . . . . . . . . . . . . . . . . . . . 41

4.21 Imaging result for a real office wall . . . . . . . . . . . . . . . . . . . . . . . . . 42

4.22 Combine the results by adding . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

4.23 Combine the results by multiplying . . . . . . . . . . . . . . . . . . . . . . . . . 43

5.1 Gantt Chart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

iv

List of Tables

3.1 Simulation parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

4.1 Experimental parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

5.1 Project progress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

5.2 Budget review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

v

Listings

A.1 Sample measurement result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

A.2 Calibration using linear regression . . . . . . . . . . . . . . . . . . . . . . . . . . 53

A.3 Sample image processing program for an empty room . . . . . . . . . . . . . . . 54

vi

Acronyms

DSTO The Defence Science and Technology Organisation. 22, 47, 48

ECal Agilent Electronic Calibration Module. 11, 12, 22

EEE Electrical and Electronic Engineering. 47

ROI Region of Interest. 4, 14, 15, 24, 27, 49

SA Synthetic Aperture. 1, 2, 14, 17, 23, 27, 29, 31, 38, 44, 50

SAR Synthetic Aperture Radar. 1, 2, 24, 27, 48–50

SNR Signal-to-Noise Ratio. 4

SVN Subversion Control. 47

TWIR Through-the-wall Imaging Radar. 1, 2, 4

VNA Vector Network Analyser. 1, 2, 4, 5, 11, 17, 22, 23, 48, 49

vii

Chapter 1

Introduction

1.1 Aims

This project titled Through-the-wall Imaging Radar was conducted to investigate the feasibility

of constructing a Synthetic Aperture Radar (SAR) using a Vector Network Analyser (VNA) as

the waveform generator and a pair of horn antennas being moved to form a Synthetic Aperture (SA),

in order to image the objects behind the wall.

1.2 Scope

The technical scope of this project was to build a simple and low cost imaging system to demon-

strate the concept and feasibility. A VNA and a SA were used for conducting experiments and

collecting data. Offline signal processing using MATLAB was employed for imaging purpose.

There was no dedicated electronic hardware used for data collection and generating image,

which reduced the complexity of the technical requirements, but imposed certain constraints

of the capability of the system. This project was to provide foundation research and work for

more complex system to be built in the future.

The scale of the project and the team (two students) was small compared to a real-world

engineering project which decreased the management complexity of the project. There was a

tight set of resource, time and budget and the project outcome is not for commercial use.

1.3 Background and Significance

A Through-the-wall Imaging Radar (TWIR) could have many applications where it is impor-

tant to view a visually and physically obstructed area. Typical applications for such radar are

search and rescue, police and military operations. The desired purpose of a through-the-wall

system is to estimate or detect the inner content and structure of a room behind the wall, or

layout of a building. Further actions, such as sending personnel inside the obscured area can be

1

followed accordingly once the result is extracted. It can be dangerous going into such situation

without much visual information about the area.

Due to need for wide range of applications, through-the-wall radar imaging has been a

research interest in recent years. Early research used a simple propagation model and imaging

algorithm while recent advances in propagation modelling and processing power have extended

the capability of TWIR, with more focus on sensor positioning and model-based 3D imaging

[1].

The use of a SA and VNA to form a SAR to image through the wall has been common

for recent research works. In [2], a mobile robot platform was designed and moved to form

the SAR. The ultra-wideband signal was generated by a VNA and two log-periodic antennas

were deployed. The system successfully imaged the objects behind sheetrock or plaster walls.

Another closely related work to our project is described in [3],[4]. The imaging radar presented

has been able to image through a single uniform wall (plywood wall) with known characteristics.

The equipments used for this work were a VNA and one horn antenna used as a transceiver.

The transmitted signal for the papers discussed was a stepped-frequency signal generated by

the VNA. The resolution of the final two dimensional images was approximately 10cm for both

down range and cross range.

Recent attempts to use a SAR to form the approach to produce three-dimensional image

of objects behind the wall can be found in [5], [6] and [7]. However, there is no notable real

experimental result presented, only simulations were conducted to test developed algorithms.

More research are certainly needed for a real implementation of such 3D imaging system.

1.4 Project overview

A simple radar with two horn antennas was built to synthesise an antenna of bigger aperture.

The VNA is utilised as a signal generator and a tool to measure the response of the environment.

Signal processing for collected measurements is implemented in MATLAB to generate the image

of an obstructed region.

The initial stage of the project was to perform necessary research and define RF components.

Horn antennas, VNA and cable were acquired for the project. The mechanical support structure

for the SAR was built. A simulation was carried out to verify initial system design and test

the feasibility. A series of experiments were then conducted to familiarise with the anechoic

chamber and the VNA, and to calibrate the radar.

The next phase of the project was to conduct a series of imaging experiments in controlled

environments with different wall materials and radar configurations. Measurements were taken

for each experiment and offline signal processing to generate images was done using MATLAB.

The analysis was performed to compare theoretical, simulation and experimental results.

The radar configuration for each experiment was bistatic or pseudo-monostatic. Walls being

investigated for the projects were a synthetic brick wall, a pin-up board, a constructed wall

2

(one and two plaster boards) and an office wall.

1.5 Document structure

This document presents a summary for the work conducted for the project. The design chal-

lenges for the radar system are discussed in Chapter 2. Initial set up and experiments, together

with simulation result are presented in Chapter 3. Chapter 4 details the experimental set-up,

the results for the experiments in controlled environments and analyses the achieved result.

Future work and direction are briefed in Chapter 5.

3

Chapter 2

Synthetic Aperture Radar Imaging

In this chapter, several design issues for TWIR will be considered including power, resolution,

calibration and image focusing. These are the key challenges during the design phase which set

this project apart from other radar systems.

2.1 Power Consideration

The imaging radar system for this project operates in the same principle with regular radar.

The electromagnetic waves will be transmitted, reflect off the object and come back to the

receiver. The received signal power must be at least bigger than the internal noise level of the

receiver in order to extract useful information about the environment. Due to the spreading

of signal in propagation from the transmitter to the receiver, the power of received signal will

be smaller when the transmitter and receiver are further away or when the objects are further

away from the radar system.

In this project, the transmitter power was limited by the VNA. The VNA acted both as a

signal generator and an equipment to measure the response between the transmitter and the

receiver. There was no dedicated hardware to amplify or control the transmitted signal power.

The range of detection for the radar was the size of Region of Interest (ROI). Typical figures

for this size are the dimension of a testing lab or a real room. The transmitted power therefore

was required to be big enough so that the signal power reflected back from an object in ROI

satisfied certain Signal-to-Noise Ratio (SNR) requirement.

By using the radar equation and assuming the transmitter and the receiver are at the same

location, the relationship between maximum detection range Ro and the transmitted power Pt

for the SNR of 10dB is:

R4o =

PtGtGrλ2σ

10(4π)3LkToB

where:

• Gt and Gr are the gains of the transmitting and receiving antennas respectively

4

• λ is the wavelength of the electromagnetic wave

• σ is the radar cross section, which is the effective scattering coefficient of the RF target

• B is the measurement IF bandwidth

• L is the system loss

• k is the Boltzmann constant

• To is the room temperature.

Typical values for the radar system parameter are VNA output power Pt = 1mW , antenna

gain Gt = Gr = 3dB, wavelength λ = 0.1m (f = 3GHz), radar cross section σ = 20cmx20cm,

IF bandwidth B = 10kHz, system loss L = 10dB. These give Ro = 21m which is reasonably

higher than the typical size of a room or a region to image.

When there is a presence of the wall between the radar system and the region to image,

due to the change of the medium as seen by the electromagnetic wave, there will be a loss and

phase change caused by the wall, which are different from them of the air gap. The calculation

above shows there is design space for further spreading or through-wall loss.

2.2 Range Resolution and Pulse Compression

Range resolution of a radar is the smallest distance between two objects in down range such

that both objects are resolvable and distinguishable. For a pulse radar, the system is able to

distinguish two objects when the return pulses from the two objects are separate. Assuming

that pulses have equal width, two receiving pulses can be distinguished when they are one pulse

width apart.

Let τ be the width of a pulse transmitted out by a pulse radar. The down-range resolution

following previous discussion is ∆R = cτ2

where c is the speed of light. Assuming that the pulse

transmitted out is a sinc pulse, the expression can be rewritten as ∆R = c2B

where B is the

frequency bandwidth of the pulse. It could be observed that good range resolution requires a

shorter pulse or in other words, a pulse of high bandwidth. The numerical requirement for the

range resolution for this project was ∆R = 10cm, which yielded a requirement for bandwidth

B = 1.5GHz.

However, it is impractical to generate a pulse of such large bandwidth (or extremely short

pulse) which would require high amount of power and dedicated hardware. A technique named

Pulse Compression was used to provide an equivalent result as one single pulse of high band-

width. This technique forms a basis for the signal generation and measurement of the VNA

used for the project. The stepped frequency signal generated by the VNA could be illustrated in

Figure 2.1. The signal sweeps through specified bandwidth and is composed of multiple pulses

5

over time. The pulses are at discrete frequencies with frequency step between two consecutive

frequencies ∆f .

Time

Frequency

∆τ

∆f

f2

f1

τ

bb

b

Figure 2.1: Stepped-frequency signal

The signal generated by the VNA is transmitted out to the environment by one horn antenna.

The reflected signal is captured by the receiving horn. The VNA compares the transmitted

and received signals and measures the reflection coefficients of the system. Let S1(f) = ST (f)

and S2(f) = SR(f) be the frequency representation of the transmitted and received signals

correspondingly, the measurement performed by the VNA can be expressed as:

S21(f) =S2(f)

S1(f)=

S∗T (f)SR(f)

|ST (f)|2

where S21(f) is the scattering parameter representing forward voltage gain. The physical mean-

ing of S21(f) is the frequency response of the environment. A typical result for scattering

coefficient S21 extracted from the VNA is shown in Figure 2.2.

6

2.5 3 3.5 4

x 109

−70

−60

−50

−40

Frequency (Hz)|S

21| (

dB)

2.5 3 3.5 4

x 109

−80

−60

−40

−20

0

Frequency (Hz)

angl

e(S

21)

(rad

)

Figure 2.2: Sample reflection measurement from VNA

The number of frequencies and the stepping size of the stepped frequency signal can be

controlled by adjusting related parameters in the VNA. In the attached figure, there are 151

frequencies from 2.5GHz to 4GHz and the step size is 10Mhz. The frequency band used was the

operating frequency band of the horn antennas. Since all the numerical figures and result are

in frequency domain, the measurements at each frequency are the loss (in dB) and the phase

change. The responses for multiple frequencies behave like a response of one single pulse of

1.5GHz bandwidth which allows better down range resolution.

2.3 Cross-range Resolution and Radar Configurations

The quality of the final image is determined by the ability to capture smaller object which can

be assessed based on the down range and cross range resolutions of the image. The criteria used

in [8] and [9] for defining cross range resolution the the half-power or 3dB width of response.

The formula for the two-way angular resolution given the aperture size D of the antenna and

the wavelength λ of the radar pulse is:

θ3dB =λ

D

Given the range from the radar to an RF target R, the cross range resolution of the image is

∆CR = RλD

. It could be seen that aperture size D is required to be high to achieve good cross

range resolution, since both R and λ are system and antenna parameters.

Typical numerical figures for our imaging radar parameters and requirement were: R = 3m,

λ = 0.1m (f = 3GHz) and ∆CR = 15cm which posed the requirement for the aperture size

D = 2m. Two horn antennas were deployed for the project and the aperture size (surface size)

7

of each horn antenna is 13cm which is much lower than the requirement. Therefore, it had been

decided that a synthetic aperture radar was built and used for our system. The radar would

have a synthetic aperture which is the effective aperture of an antenna linear array formed by

moving the horn antenna. There are two modes to configure the SA array elements which can

yield different results in final imaging: pseudo-monostatic and bistatic configurations.

For pseudo-monostatic configuration, the two horn antenna are put close together such

that the distance between them is small compared to the target range. This distance is kept

unchanged when the horn antennas are moved to form the SA or in other words, both horns

are moved simultaneously. The process of moving two horn antennas is illustrated in Figure

2.3. This configuration is not strictly monostatic since the two horn antennas cannot be put at

the same location due to the mechanical support structure.

RxTx

RxTx

RxTx

RxTx

RxTx

. . .

Figure 2.3: Monostatic configuration

For bistatic configuration, only one horn is moved to form the SA. The transmitting horn is

kept static at the same location. The distance between two antennas can be varied and assumed

to be big compared to the target range. The graphical illustration for this configuration is shown

in Figure 2.4.

8

TxRx

TxRx

TxRx

Tx Rx

Tx Rx

. . .

Figure 2.4: Bistatic configuration

It could be seen from the description above that when a horn antenna is moved, the distance

from it to the other horn antenna, via a pixel of interest is changed. The electromagnetic path

change in pseudo-monostatic case is bigger than it of bistatic case. For comparison, the distance

from transmitting horn to receiving horn via pixel Pi(1m, 3m) for both cases is sketched in

Figure 2.5. For bistatic configuration, am = 0 and bm = 0.2 → 1.6m and for pseudo-monostatic

case, bm = 0.2 → 1.6m and am = bm −0.2m, where am and bm are the locations of two antennas

in the array. These numbers are chosen only for illustration and are not the real parameters of

the system. It could seen that the pseudo-monostatic configuration provides greater variation

in path length compared to bistatic case. The effect of this difference can result in the difference

in the cross range resolution for the two configurations.

bm (m)

d(am, (1, 3), bm) (m)Monostatic

Bistatic

0 0.2 1.6

6.27

6.09

Figure 2.5: Distance from Horn 1 to Horn 2 via pixel Pi for monostatic and bistatic cases

9

2.4 Calibration

2.4.1 Overview

The initial step for generating a 2D image is to extract a correct range profile for each arrange-

ment of the two horn antennas. The range profile is effectively the impulse response of path

of interest. A simple experiment using two directly facing horns (Figure 2.6) was set up for

extracting the range profile and double-checking the design parameters (range and power).

Horn 1

Agilent VNA

Horn 2

r r

r r

d

Figure 2.6: 1D experiment set up

The ideal result for the forward voltage gain S21 or S12 is the phase shift corresponding to

the distance between antennas in frequency domain or the spike at this distance in the range

profile. Sample range profiles from collected data are sketched in Figure 2.7.

0 5 10 15 20

1

2

3

4

5

6

x 10−4

Range (m)

ho

Range Profile (note: d = 5.34m)

(a) d = 5.34m

0 5 10 15 20

1

2

3

4

5

6

7

8

9

10

x 10−4

Range (m)

ho

Range Profile (note: d = 4.15m)

(b) d = 4.15m

Figure 2.7: Impulse responses for different antenna separations

It could be seen that the peaks in both range profiles were shifted away from desired locations.

And importantly, the relative shift in peak locations between any two range profiles is equal to

the relative change of the distance between the two horns. By dividing the two responses in

frequency domain, the response representing relative phase shift or time delay can be extracted

as shown in Figure 2.8.

10

0 1 2 3 4 5

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0.55

Range (m)

ho

Range Profile δd = 5.34 − 4.15 = 1.19m

Figure 2.8: Relative response between two separations

Therefore, a reference response of a known distance is needed to correctly retrieve the desired

range profile or in other words, calibration is required. Furthermore, the shift of peak location

above is explained by introducing the system delay to caused by cables, instrument and horn,

which is independent of the antenna separation (Figure 2.9). Therefore, if system delay to is

known, it can be calibrated out by providing equivalent phase shift to the original response.

Delay t

h(t)

dc to + d

c

Actual

Desired

Figure 2.9: Desired vs. Actual delays

2.4.2 Calibration using Electronic Calibration Kit

The Agilent Electronic Calibration Module (ECal) is available for project, which is included

with the VNA (Figure 2.10). It has two ports and acts as the connector between two cables

and the VNA during calibration process.

11

Figure 2.10: Electronic Calibration kit

Since the cable introduces amplitude loss and phase change towards the final response of the

system, the ECal provides an automatic calibration tool which is to remove systematic loss and

delay caused by equipment and cables. The loss and phase change of one N cable is attached

for illustration in Figure 2.11. After the calibration, the VNA remembers the response of the

cables and automatically changes the measurement accordingly to give the correct response of

the system. The delay is removed in the calibrated response or the spike in time domain is

brought closer to correct location.

2.5 3 3.5 4

−4.4

−4.2

−4

−3.8

−3.6

−3.4

Frequency (GHz)

|Sca

ble| (

dB)

Amplitude

2.5 3 3.5 4

−300

−200

−100

0

Frequency (GHz)

angl

e(S

cabl

e) (r

ad)

Phase

(a) Loss and phase change in the cable

1 2 3 4 5 6 7 8 9 10

x 10−8

2

46

810

1214

x 10−3

Delay (s)

h 12

Original response

1 2 3 4 5 6 7 8 9 10

x 10−8

0.005

0.01

0.015

0.02

0.025

Delay (s)

h 12 c

al

Calibrated response

(b) Original and calibrated responses

Figure 2.11: Cable response and calibration result using ECal module

2.4.3 Calibration using Linear Regression

When two horn antennas were used as a transmitter and a receiver for SAR configuration, it was

observed that there is remaining unknown delay in the response. It was suggested that further

calibration would be carried out using linear regression analysis which is briefed in Figure 2.12.

This is to reduce systematic and measurement errors and to detect an outlier if there is one.

The location of highest peak in the impulse response was identified for each distance between

two horn antenna. Linear regression using least squares approach with one dependent variable

12

(distance) is fitted to experimental data points. Intersection between best-fit line and y-axis is

the system delay to. The slope of fitting curve is expected to be 1/c where c is the speed of

light in air.

d

τ

b

b

b

b

d1 d2 d3 d4

to

0

Figure 2.12: Linear Regression for calibration

Sample linear regression result using real experimental data is attached in Figure 2.13 for

demonstration. The correlation coefficient is 0.9989 which proves the correctness of linear

model and the assumption on independent system delay. The reciprocal of the slope is (3.44 ×

10−9)−1 ≈ 2.91 × 108m/s which is reasonably close to speed of light in air. Linear regression

proved feasible for calibration and was used to calibrate system delay. For each experimental

session, calibration process was repeated to ensure the correct result if there was any change

in the set up of the system.

0 0.5 1 1.5 2 2.5 3 3.5 40

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

x 10−8

Distance between antennas (m)

Del

ay w

ith n

o ca

libra

tion

(s)

Delay vs. Separation (May 3rd)

Correlation coefficient R = 0.9989

Collect dataFitted data: delay = 3.44e−009*distance + 2.59e−009

Figure 2.13: Sample experimental result for linear regression

13

S̃21

ej2πfto

S21

Figure 2.14: Calibration technique

When unknown delay to is found, a simple multipli-

cation operation is performed on original gain measure-

ment S21 or S12 as in Figure 2.14. The output is the

frequency response of the airgap between two antennas.

The difference between output and input is the in-

crease in phase or the location of peak in time domain

representation is brought closer to zero. The sample

result to demonstrate this effect is attached in 2.15.

0 2 4 6 8 100

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.018

Range (m)

h d

Range profile without calibration (note: correct d = 0.82m )

← d = 1.6

(a) Without calibration

0 2 4 6 8 100

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

Range (m)

h d

Range profile (note: correct d = 0.82m )

← d = 0.8

(b) With calibration

Figure 2.15: Pre- and post-calibration impulse response

The distance between two horns for the experiment was 0.82m and the peak of impulse

response was located at 0.8m. This means that the proposed calibration approach performed

well and recovered the correct range profile for the air gap.

2.5 Focusing Technique

2.5.1 Focusing Delay Formulation

2.5.1.1 When there is no wall

The ROI of our imaging system was a single 2D slice of the room at the height of the SA. A

two-dimensional Cartesian coordinate system is fitted into this slide for our imaging purpose,

as seen in Figure 2.16. Axes x and y represent cross-range and down-range respectively. Two

horn antennas are put at (am, 0) and (bm, 0) where subscript m stands for a measurement. It

is noted that there are different measurements for different locations of the antennas. The

inter-element spacing for the synthetic aperture radar is denoted as ∆. Horn 1 can be used as

a transmitter and Horn 2 is a receiver or vice versa.

14

x

y

0b b b

amb b

. . .bbm

b b b

Horn 1 Horn 2

Pixel pi(xi, yi)

∆

Figure 2.16: 2-D imaging system configuration

The pixel size of the ROI is (δx, δy) such that there is no significant improvement in the result

if the pixel is divided smaller. This figure is important to maintain a reasonable computational

complexity and to reduce processing time. The smaller the size of the pixel is, the more time it

would take to image ROI. The simulation was carried out to select the appropriate pixel size.

The value was chosen to be smaller than simulated range and cross range resolutions.

Consider an arbitrary pixel Pi which has the bottom left corner of coordinates (xi, yi), the

electromagnetic distance from the transmitter to the receiver via pixel Pi is simply the sum of

two Euclidean distances between Pi and the transmitter, and between Pi and the receiver:

d(am, (xi, yi), bm) = d(Horn 1 → Pi) + d(Pi → Horn 2)

=√

(xi − am)2 + y2i +

√

(xi − bm)2 + y2i

2.5.1.2 When there is a wall

When there is a wall between the radar and the region of interest, the electromagnetic path

from transmitting horn to receiving horn via a pixel behind the wall is changed. Due to the

change of medium in transmission, there is refraction occurring at the two wall-air surfaces.

The bending effect on the electromagnetic rays caused by refraction is illustrated in Figure

2.17.

15

x

y

0b b b

amb b

. . .bbm

b b b

Horn 1 Horn 2

Pixel pi(xi, yi)

∆

Wallt, n

yo

yo + t

Figure 2.17: 2-D imaging system configuration with wall

Let t and n be the thickness of the wall and the refractive index of the wall material corre-

spondingly. Without loss of generality, only one path from one horn to the pixel is considered

as in Figure 2.18. The calculation for the other path can be carried out in a similar manner.

x

y

0b b b

amb b

Horn 1

Pixel pi(xi, yi)

Wallt, n

yo

yo + t

x1 x2 xi

yi

θ1

θ2

θ1

Figure 2.18: 2-D imaging system configuration with wall

By Snell’s law, the relationship between angles of incidence and refraction is:

sin θ1 = n sin θ2

16

By geometry, the following is extracted:

(yi − t) tan θ1 + t tan θ2 = xi − am

By solving the equations above, angles θ1 and θ2 can be found and one-way focusing path

is:

d(am, (xi, yi)) =y − t

cos θ1+

nt

cos θ2

However, the symbolic and analytic solution as discussed above is hard to derive. Further-

more, the processing is carried out by computer program. Hence numerical analysis to find the

focusing path is preferred. An equivalent approach to Snell’s law using Fermat’s principle of

least time was proposed and used for this project. The principle states that the electromagnetic

path between any two points is the path of least time. As a result, the problem of finding the

angles as above can be turned into an optimisation problem to find the coordinates of points

where the ray meets the wall surfaces, x1 and x2. The optimal value for mentioned coordinates,

x̂1 and x̂2 are chosen to minimise the electromagnetic path d, where:

d(am, (xi, yi)) =√

(x̂1 − am)2 + y2o + n

√

(x̂2 − x̂1)2 + t2 +√

(xi − x̂2)2 + (y − yo − t)2

The focusing path from the pixel (xi, yi) to horn antenna (bm, 0) can be calculated which

gives us the final return focusing delay τ for imaging purpose:

τ =d(am, (xi, yi)) + d((xi, yi), bm)

c

where c is the speed of light.

2.5.2 Imaging implementation

For all position of horn antennas in both SA configurations, either bistatic or pseudo-monostatic,

measurement for Sambmcan be made using the VNA, where S can be either S21 or S21 and am

and bm are the x-coordinates for horn 1 and horn 2. However, these reflection measurement

only gives the response of whole region of interest. To find imaging value for a pixel of the

region, focusing technique was used, either in Time Domain or Frequency Domain.

2.5.2.1 Time domain implementation

As discussed before, if there is an object at pixel Pi, the peak of the range profile will be located

at the range which is exactly the distance from one horn to the other horn via Pi. This distance

forms an ellipse (its foci are two horns) that the object can stay on, which means exact object

location can not be determined using one range profile. However, if there is an object at pixel

Pi, above discussion will always true for any configuration of the two horns. In other word,

17

different range profiles form different ellipses which theoretically have one intersect at Pi.

The result of calibrating the measurement reflection is the response without system delay.

The inverse Fourier Transform operation performed returns its time domain representation -

range profile. It is proposed that for each pixel in the region of interest, its imaging value

is the sum of all range bins from different range profiles. Bin location for range profile m is

determined by using:

nm = [d(am, (xi, yi), bm

c/B]

where c/B is the smallest quantisation level in range, B is the frequency bandwidth and [·]

denotes rounding operation.

Since the result of the summation for each bin is complex, its magnitude is taken for the

final image. The mathematical expression for the imaging value calculation for each pixel is:

I(xi, yi) = |N

∑

m=1

hambm(nm)|

The block diagram in Figure 2.19 shows the procedure for imaging using time domain data.

Sa1b1

Sa2b2

Sambm

SaN bN

IFFT

IFFT

IFFT

IFFT

r

r

r

r

r

r

r

r

r

Bin

Sel

ecti

on

nm

=[d

(am

,(x

i,y

i),

b mc/

B]

...

...

...

...

|(·)| I(xi, yi)

ha1b1

ha2b2

hambm

haN bN

ha1b1(n1)

ha2b2(n2)

hambm(nm)

haN bN(nN)

Figure 2.19: Imaging technique in time domain

It is noted that due to the quantisation effect caused by the rounding operation, the ellipse

formed by particular range using one range profile is thicken which could result in a region of

intersection instead of intersecting point when considering multiple range profiles.

18

2.5.2.2 Frequency domain implementation

An equivalent approach in frequency domain is proposed for imaging objects. The distance

between the peak and the origin in a range profile in time domain is equivalent to the phase

difference in frequency domain. The quantitative value for this phase difference is φ = −2πfd/c

where f is a single frequency, d is the distance between peak and origin or the distance between

two horns via an object and c is the speed of light in air. This also means that for each

reflection response, if an increasing phase shift is applied so that it can compensate φ, the

response will theoretically a response of no phase shift (or peak is brought back to time origin).

Therefore, for a pixel Pi, if all compensated responses have phase shifts of zero, they can be

added constructively when there is an object at Pi. If compensated responses have non-zero

phase shifts, sum of response is destructive or there is no object at Pi.

The implementation procedure is described in Figure 2.20. It is noted that the image can

be formed using one single frequency though it will be summed across all operating frequencies

to form a finer image. The final image is formed by taking magnitude value of the complex

image.

Sa1b1

Sa2b2

Sambm

SaN bN

...

...

ej2πfd(a1,(xi,yi),b1)/c

ej2πfd(a2,(xi,yi),b2)/c

ej2πfd(am,(xi,yi),bm)/c

ej2πfd(aN ,(xi,yi),bN )/c

∑

f|(·)| I(xi, yi)

Figure 2.20: Imaging technique in frequency domain

The mathematical expression for the implementation in frequency domain is the inverse

Fourier Transform of the sum of all shifted responses:

I(xi, yi) =

B∑

f=0

( N∑

m=1

Sambmej2πfd(am,(xi,yi),bm)/c

)

ej2πfτ/B

∣

∣

∣

∣

τ=0

19

or

I(xi, yi) =B

∑

f=0

N∑

m=1

Sambmej2πfd(am,(xi,yi),bm)/c

The logical flow of the implementation in MATLAB can be described as follow:

for each pixel P(x,y) in the region of interest

initialise the sum So (length of B/delta_f)

for each location of antennas (a,0) and (b,0)

calculate the focusing distance from horn 1 to horn 2, via pixel P

phase shift the response S by the focusing delay to get S’

add S’ to the sum So

sum So across all frequencies

get the amplitude for imaging

2.6 Assumptions

Since the main objective of this project was using simulation and experiment to prove concept

and test the feasibility, the following assumptions were made about the radar system and the

environment to be imaged:

• System was linear and invertible which means multipath reflection, diffraction, dispersion

or near field artifact were insignificant.

• Objects to be imaged were metallic, static and distinct. The resultant images of this

project would provide tool to detect and localise objects behind the wall. Therefore, the

objects should not be RF transparent or either moving. This was to avoid localisation

error and image blurring.

• Wall was uniform and isotropic. The propagation model through the wall was linear and

only valid when the wall was of uniform thickness. The front and back surfaces of the

wall were assumed to be parallel. The wall is assumed to partially allow RF wave pass

through or in other words, electromagnetic shielding wall was not of our interest.

• There was no real-time requirement. The designed imaging radar was not time-critical

which means experimental data was collected and imaging processing was performed

offline. The requirements for software and hardware were therefore much simpler and

achievable within given time frame.

20

Chapter 3

Experimental Set-up and Initial

Experiments

3.1 Equipments and Experimental Environment

There were two horn antennas available to construct a synthetic aperture. The operating

frequency for both horns is from 2.5GHz to 4GHz. To hold and move each or both horn

antennas to form the synthetic aperture, a support structure was designed and built. The

mechanical support provided flexibility in choosing location for each horn (by sliding) while

ensured the whole system was stable for experiment. The width of the support structure was

limited by the width of the anechoic chamber as seen in Figure 3.1(a).

(a) SAR (b) Agilent PNA

Figure 3.1: Synthetic aperture radar and Agilent PNA (VNA)

The anechoic lab consists of a chamber and an open space and both of which were used

for the imaging experiments. Wall and floor of the chamber are filled with absorptive material

which reduces reflection and limit noise from outside environment. The VNA available in the

lab was the 2-ports Agilent N5230A PNA-L Network Analyser (Figure 3.1(b)) which has a

21

ECal module. This module was used to pre-calibrate system noise and delay of external cables.

Horn antennas were borrowed from The Defence Science and Technology Organisation (DSTO).

To connect the horn antenna to the VNA port and ECal module, two N-type cables (5 metres

each) and several N-to-SMA adaptors were borrowed from EEE School laboratory.

(a) ECal module (b) Horn antennas

Figure 3.2: ECal module and DSTO horn antennas

3.2 Experiment with Patch Antenna

A cross-polarised patch antenna with dual feeds as seen in Figure 3.3(a) was used to familiarise

with the VNA. Main aim of the experiment was to measure the forward voltage gain S12 (or

S21) of the antenna using VNA when input signal was put into one feed and output signal was

taken out of other feed. The expected behaviour of the response is low gain in frequency range

of operation with narrow bandwidth and higher gain for other frequencies. The capabilities

of the VNA (Rohde & Schwarz ZVL model - Figure 3.3(b)) such as scattering measurement,

stepped-frequency signal generation or file saving were tested.

(a) Patch Antenna (b) Rohde & Schwarz ZVL VNA

Figure 3.3: Patch antenna and R&S ZVL VNA

22

Data collected from VNA was used for offline processing using MATLAB to reproduce

frequency response plot and to find impulse response using Inverse Fourier Transform. Plots

are attached in Figures 3.4 and 3.5.

0.5 1 1.5 2 2.5

x 109

−45

−40

−35

−30

−25

−20

−15

−10

−5

0

Frequency (Hz)

Mag

nitu

de R

espo

nse

|H| (

dB)

Frequency response (Magnitude) of the cross−polarised patch antenna

(a) Amplitude

0.5 1 1.5 2 2.5

x 109

−70

−60

−50

−40

−30

−20

−10

0

Frequency (Hz)

Pha

se R

espo

nse

angl

e(H

) (r

ad)

Frequency response (Phase) of the cross−polarised patch antenna

(b) Phase

Figure 3.4: Forward voltage gain for a cross-polarised patch antenna

0 0.2 0.4 0.6 0.8 1

x 10−7

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16 X: 3.339e−009Y: 0.1682

Time (s)

h =

ifft(

H)

Delay profile of the cross−polarised patch antenna

Figure 3.5: Impulse response for a cross-polarised patch antenna

It could be seen from the result that the operation bandwidth is narrow, with a destructive

resonance at around 1.5GHz. The antenna also has linear phase property which represents

approximate equal delays between two ports of the VNA for the used frequency range. The

impulse response gave the delay τ ≈ 3.34ns or equivalent air gap of 1m. The results proved

the feasibility of using the reflection measurement for 1-D imaging purpose.

3.3 Simulation

To test the proposed SA configurations and processing methods, a MATLAB-based simulator

was built. A reference response with no phase shift was extracted from the real experiment.

23

For each transmitter and receiver location, a simulated reflection measurement was created by

phase-shifting reference response. The shifting amount is corresponding to the electromagnetic

distance from transmitter to receiving antenna via simulated object. The simulated responses

were then used for generating image of region of interest. The variable parameters in the

simulator are: size of region of interest, length and element spacing for SAR and object location.

Other parameters for stepped-frequency signal were taken from real data. The simulation was

run using parameters that are relevant to the real SAR and conducted experiments. Table 3.1

lists values that were used in the simulation of which the result is attached in Figures 3.6 and

3.7.

Parameters Value Note

Bandwidth B 1.5GHz (2.5 → 4GHz) Fixed

Frequency step δf 10MHz Fixed

No. of frequencies 151 Fixed

Range of unambiguity c/δf 30m Fixed

Pixel size 1cmx1cm Fixed

Size of ROI 1.6mx6m Variable

SAR aperture 1.6m Variable

Array element spacing ∆ 0.04m Variable

Object location (1m,3m) Variable

Table 3.1: Simulation parameters

The following could be observed from the simulation results:

• The frequency domain implementation gave smoother down range and cross range profiles

while the time domain technique suffered from quantisation effect which made the profiles

look discrete.

• The cross range resolution for monostatic configuration was smaller compared to it of

bistatic configuration. This result can be observed in both time domain and frequency

domain implementations: 3dB width of 10cm for monostatic and of 15cm for bistatic

approximately.

• The chosen pixel size (1cmx1cm) is reasonable since it is much smaller than both range

and cross range resolutions.

The simulation result proved the feasibility of using designed system parameters for real

experiments. The frequency domain implementation was used for real imaging experiment due

to its advantage over time domain implementation.

24

Cro

ss−

Ra

ng

e (

cm

)

Range (cm)

monostatic, time domain processing, object is at x = 1.00m y = 3.00m

100 200 300 400 500 600

20

40

60

80

100

120

140

160

(a) Monostatic - 2D image

280 290 300 310 320−15

−10

−5

0

y [Range (cm)]

I(y)

(dB

)

Range profile at x = 100 cm

50 100 150 200−20

−18

−16

−14

−12

−10

−8

−6

−4

−2

0

x [Cross Range (cm)]

I(x)

(dB

)

Cross Range profile at y = 301 cm

(b) Monostatic - profiles

Cro

ss−

Ra

ng

e (

cm

)

Range (cm)

bistatic, time domain processing, object is at x = 1.00m y = 3.00m

100 200 300 400 500 600

20

40

60

80

100

120

140

160

(c) Bistatic - 2D image

260 280 300 320 340−15

−10

−5

0

y [Range (cm)]

I(y)

(dB

)


0 50 100 150 200−20

−18

−16

−14

−12

−10

−8

−6

−4

−2

0


I(x)

(dB

)


(d) Bistatic - profiles

Figure 3.6: Simulation result for time domain implementation

Cro

ss−

Ra

ng

e (

cm

)

Range (cm)

monostatic, frequency domain processing, object is at x = 1.00m y = 3.00m

100 200 300 400 500 600

20

40

60

80

100

120

140

160

(a) Monostatic - 2D image

280 290 300 310 320−15

−10

−5

0

y [Range (cm)]

I(y)

(dB

)


80 90 100 110 120−20

−18

−16

−14

−12

−10

−8

−6

−4

−2

0


I(x)

(dB

)


(b) Monostatic - profiles

Cro

ss−

Ra

ng

e (

cm

)Range (cm)

bistatic, frequency domain processing, object is at x = 1.00m y = 3.00m

100 200 300 400 500 600

20

40

60

80

100

120

140

160

(c) Bistatic - 2D image

280 290 300 310 320−15

−10

−5

0

y [Range (cm)]

I(y)

(dB

)


60 80 100 120 140−20

−18

−16

−14

−12

−10

−8

−6

−4

−2

0


I(x)

(dB

)


(d) Bistatic - profiles

Figure 3.7: Simulation result for frequency domain implementation

25

Chapter 4

Imaging Experiments and Results

Once the design phase was completed and simulation gave the expected results, the experiments

to image the objects within a region of interest were carried out. This chapter details the

conducted experimental set up and results for the cases of no wall and with a wall. Various

wall materials were investigated, including pin-up board, contructed wall using plaster boards

and real office wall.

4.1 Experimental Procedure

For each experiment, the following steps were done in order to generate a 2-D image of the

room:

• Calibrate the system by using Agilent Electronic Calibration Module and linear regression

technique.

• Measure and record physical locations of the wall and the objects in the controlled envi-

ronment. These figures were used to evaluate the performance of the imaging radar.

• Move the horn antennas to form a Synthetic Aperture. The fashion of moving the horns

was based on the chosen configuration: monostatic or bistatic. For each movement, the

response of the environment was measured and stored into data storage.

• Apply frequency domain implementation of focusing to generate a 2-D image using

recorded data. MATLAB programs were written for this step and Sample code used

can be found in A.

• Analyse the imaging result, including the appearance of objects in the image and range

and cross range profiles at different coordinates. The range and cross range resolutions

were compared against the theory and simulation results.

Objects are paint cans with cross section of diameter of 23cm. The parameters used for the

experiments are listed in Table 4.1.

26

Parameters Value

Bandwidth B 1.5GHz (2.5 → 4GHz)

Frequency step δf 10MHz

No. of frequencies 151

Range of unambiguity c/δf 30m

Power at transmitting port 10dBm

IF bandwidth 10kHz

Samples for averaging 100

Signal sweeping time 14.745ms

Pixel size 1cmx1cm

Size of ROI 1.6mx6m

SAR aperture D 1.6m

Array element spacing ∆ 0.04m

Bistatic case am = 0m or 0.8m or 1.6m, bm = 0.16 → 1.6m

Pseudo-monostatic case am = 0 → 1.44m, bm = am + 0.16m

Table 4.1: Experimental parameters

The experiments for no wall case and the pin-up board were conducted in the anechoic

chamber. The experiments for constructed wall were conducted in Final Year Lab. Two offices

in Engineering Maths Building were used for the office wall experiments.

4.2 Imaging of objects without wall

4.2.1 1-object imaging

The images attached in Figure 4.1 are result of processing in frequency domain with two different

SA configurations. The object is correctly located in imaging result for pseudo-monostatic

configuration but not for bistatic case.

27

Cro

ss−

Ran

ge (

cm)

Range (cm)

2−D projection, object is at (70, 375)

100 200 300 400 500 600

20

40

60

80

100

120

140

160

(a) Pseudo-monostatic configuration

Cro

ss−

Ran

ge (

cm)

Range (cm)

2−D projection, object is at (70, 375)

100 200 300 400 500 600

20

40

60

80

100

120

140

160

(b) Bistatic configuration

Figure 4.1: Experimental result for one object at (70cm, 375cm) in the anechoic chamber

By locating the peak’s coordinates of the image in pseudo-monostatic case, the down range

and cross range profiles can be extracted as in Figure 4.2. It is noted that the x direction

represents cross range and y direction represents down range.

0 100 200 300 400 500−30

−25

−20

−15

−10

−5

0

y [Range (cm)]

I(y)

(dB

)

Range profile at x = 71cm

(a) Down-range profile

10 20 30 40 50 60 70 80 90 100 110−30

−25

−20

−15

−10

−5

0


I(x)

(dB

)

Cross Range profile at y = 364cm

(b) Cross-range profile

Figure 4.2: Down-range and cross-range profiles at peak location

The physical measurement prior to the experiment gave the location of the object: (70cm,

375cm). However, the location of the peak in the final image is at (71cm, 364cm). If the image

resolution is considered as the two-way 3dB width of the range or cross range profile which is

the distance between -3dB points, Figure 4.2 gives:

Range resolution ∆y ≈ Cross-range resolution ∆x ≈ 10cm

These figures are comparable to or even better than expected results:

∆ytheory =c

2B= 10cm

28

and

∆xtheory ≈ yλ

D≈ 20cm for f = 3GHz

The real object location falls into 3dB region down from the peak. Experimental results were

as expected and showed that processing in frequency domain was the right approach for the

imaging implementation in the following stages of the project.

4.2.2 2-object imaging

This section presents the result for similar experiment with the presence of two objects at two

different locations. It is noticed that due to the effect of antenna array beam pattern in the

case of same down range (Figure 4.3) or the effect of attenuation in power reflected in the case

of different down ranges (4.6(a)), one object appears stronger in the image compared to the

other. For the experiment of two objects at same cross range (Figure 4.6(b)), one object cannot

be resolved due to the fact that transmitting waves were mostly reflected by the object in front

of it and hence the reflection from this object became insignificant.

Cro

ss−

Ran

ge (

cm)

Range (cm)

2−D projection, objects are at (22,375) and (80, 375)

100 200 300 400 500 600

20

40

60

80

100

120

140

160

Figure 4.3: Experimental result for two objects at (80cm, 375cm) and (22cm, 275cm) in the

anechoic chamber (pseudo-monostatic configuration)

Range and cross range profiles at the local peaks when two objects are at the same range

are attached in Figures 4.5 and 4.4. The range and cross range resolutions of the image can

be computed and they are approximately the same as in the case of one object imaging. The

presence of the wall between the SA and the object is an increase in the level of sidelobes in

the cross range profile.

29

0 100 200 300 400 500−30

−25

−20

−15

−10

−5

0

y [Range (cm)]

I(y)

(dB

)


(a) Down range profile – object at (80cm, 375cm)

0 100 200 300 400 500 600−30

−25

−20

−15

−10

−5

0

y [Range (cm)]

I(y)

(dB

)


(b) Down range profile – object at (22cm, 375cm)

Figure 4.4: Down range profiles at peak location for image of 2 objects

0 20 40 60 80 100 120 140 160−30

−25

−20

−15

−10

−5

0


I(x)

(dB

)


Figure 4.5: Cross range profile at peak location for image of 2 objects

Cro

ss−

Ran

ge (

cm)

Range (cm)


100 200 300 400 500 600

20

40

60

80

100

120

140

160

(a) Objects at (24cm, 239cm) and (70cm, 369cm)

Cro

ss−

Ran

ge (

cm)

Range (cm)


100 200 300 400 500 600

20

40

60

80

100

120

140

160

(b) Objects at (80cm, 303cm) and (80cm, 379cm)

Figure 4.6: Imaging results for two objects at different ranges (pseudo-monostatic)

30

4.3 Imaging result for a pin-up board

To synthesise a wall in an controlled environment, a pin-up board with thickness of 1cm was

used for setting up the experiment. A paint can was put at known location in the room and

the VNA was also in the region of imaging. The imaging results for both SA configurations

are attached in Figures 4.7 and 4.8. In each figure, the 2-D image of the region of interest in

linear scale and the range and cross range profiles at the peak location are shown. It is noted

that the pin-up board was not big enough to form a full wall, but the object was arranged so

that it could not be seen by the SA.

The 2-D images for both configurations and their range and cross range profiles were analysed

and the following results are noticed:

• For pseudo-monostatic configuration

– The imaging peak is at (76cm, 239cm) which is relatively close to the real object

location (80cm, 255cm)

– The whole wall is resolved in the final image and its image is thicker than 1cm.

– The range and cross range resolutions are both approximately 10cm.

– The imaging value of the wall is about 5dB lower than it at the object location.

• For bistatic configuration - static horn was put at x = 0cm

– The imaging peak is at (82cm, 248cm) which is relatively close to the real object

location (86cm, 255cm)

– Only part of the wall is resolved in the final image and its image is thicker than 1cm.

The resolved part was directly in front of the static horn. The characteristics of the

radiation pattern of the horn antenna could be used to explain this pattern. Due to

the fall-off in the radiation and reception patterns, the reflection off the wall as seen

by the receiver was only strong when the two horn antennas were spatially close.

– The range resolution is approximately 10cm while the cross range resolution is

roughly 15cm, which is lower compared to the pseudo-monostatic case.

• The blurry region appeared in the 2-D images of both configurations, behind the wall and

the object is the image of the VNA.

31

Cro

ss−

Ran

ge (

cm)

Range (cm)

2−D projection, object is (80cm, 255cm), wall is at y = 127 cm

100 200 300 400 500 600

20

40

60

80

100

120

140

160

(a) 2D image

0 50 100 150 200 250 300 350 400 450−30

−25

−20

−15

−10

−5

0

y [Range (cm)]

I(y)

(dB

)


(b) Range profile

40 50 60 70 80 90 100 110 120 130−30

−25

−20

−15

−10

−5

0


I(x)

(dB

)


(c) Cross range profile

Figure 4.7: Result for pin-up board – Pseudo-monostatic

Cro

ss−

Ran

ge (

cm)

Range (cm)

2−D image, object is (86cm, 255cm), pin board is at y = 135cm

100 200 300 400 500 600

20

40

60

80

100

120

140

160

(a) 2D image

0 100 200 300 400 500−30

−25

−20

−15

−10

−5

0

y [Range (cm)]

I(y)

(dB

)


(b) Range profile

0 50 100 150−30

−25

−20

−15

−10

−5

0


I(x)

(dB

)



Figure 4.8: Result for pin-up board – Bistatic

32

4.4 Imaging result for a constructed wall

4.4.1 Set up

A wall using plaster boards and timber studs was constructed for this project. The plaster

boards have thickness of 1cm. The location of the stud in the wall were chosen so that the

constructed wall would be the same as a plaster wall in commercial use.

The following experiments were conducted to study the performance of the imaging radar

with the constructed wall:

• Imaging an open space with no wall and no object.

• Imaging a region with no wall.

• Imaging a region with a single layer wall formed by one plaster board.

• Imaging a region with a double layer wall formed by two plaster boards and a stud frame.

The experimental set-up and controlled environment could be seen in Figure 4.9.

(a) No wall (b) One plaster board

(c) Stud frame (d) Two plaster boards

Figure 4.9: Experimental set up for constructed wall

33

4.4.2 Empty room

The result for the imaging experiment for the empty room is shown in Figure 4.10. The SA

configuration used for this experiment was pseudo-monostatic. An unknown repeating pattern

which appeared in the imaging result has not been explained. It could be due to the cluster

around the test area or the internal structure of the room.

Cro

ss−

Ran

ge (

cm)

Range (cm)

2−D image, empty room

100 200 300 400 500 600

20

40

60

80

100

120

140

160

(a) 2D image - linear

Cro

ss−

Ran

ge (

cm)

Range (cm)

2−D image, empty room, log scale

100 200 300 400 500 600

20

40

60

80

100

120

140

160

(b) 2D image - logarithmic

Figure 4.10: Imaging result for an empty controlled room

4.4.3 No wall

The result for the imaging experiment when there were two paint cans in the region to image

is shown in Figure 4.11. The pattern which appeared in the above experiment could be again

observed in the 2-D imaging result. However, the pattern was stronger in bistatic configuration

compared to monostatic case.

Cro

ss−

Ran

ge (

cm)

Range (cm)

2−D image, objects are at (140,383) and (63,225), log scale

100 200 300 400 500 600

20

40

60

80

100

120

140

160

(a) 2D image – pseudo monostatic

Cro

ss−

Ran

ge (

cm)

Range (cm)


100 200 300 400 500 600

20

40

60

80

100

120

140

160

(b) 2D image – bistatic

Figure 4.11: Imaging result for controlled environment without wall

The range and cross range profiles of the coordinates of the peaks for both configurations

are shown in Figures 4.12 and 4.13.

34

0 100 200 300 400 500 600−30

−25

−20

−15

−10

−5

0

y [Range (cm)]

I(y)

(dB

)


(a) Range profile - Object 1

20 30 40 50 60 70 80 90−30

−25

−20

−15

−10

−5

0


I(x)

(dB

)


(b) Cross range profile - Object 1

0 100 200 300 400 500 600−30

−25

−20

−15

−10

−5

0

y [Range (cm)]

I(y)

(dB

)


(c) Range profile - Object 2

0 20 40 60 80 100 120 140 160−30

−25

−20

−15

−10

−5

0


I(x)

(dB

)


(d) Cross range profile - Object 2

Figure 4.12: Imaging profiles for pseudo-monostatic configuration

0 100 200 300 400 500 600−30

−25

−20

−15

−10

−5

0

y [Range (cm)]

I(y)

(dB

)



0 20 40 60 80 100 120 140−30

−25

−20

−15

−10

−5

0


I(x)

(dB

)



0 100 200 300 400 500 600−30

−25

−20

−15

−10

−5

0

y [Range (cm)]I(

y)

(dB

)



0 20 40 60 80 100 120 140 160−30

−25

−20

−15

−10

−5

0


I(x)

(dB

)



Figure 4.13: Imaging profiles for bistatic configuration

35

The results observed from 2-D images, range and cross range profiles are as follows:

• The physical measurement of the test area gave the location of the paint cans: (140cm,

383cm) and (63cm, 225cm). The locations of the peaks for pseudo-monostatic configu-

ration are (131cm, 371cm) and (60cm, 213cm). The locations of the peaks for bistatic

configuration are (131cm, 370cm) and (60cm, 213cm).

• The range and cross range resolutions at the peaks do match with the results of the

simulation and previous experiments.

• The second object (further from the SA) is just resolvable since it stays closer to the

unknown patterns as discussed above.

4.4.4 One plaster board

The experimental result for when there was a single wall of one plaster board is shown in

Figure 4.14. The down range and cross range profiles at the coordinates of the peaks for both

SA configuration are attached in Figure 4.15 and 4.16.

Cro

ss−

Ran

ge (

cm)

Range (cm)

2−D image, objects are at (128,333) and (59,203), linear scale

100 200 300 400 500 600

20

40

60

80

100

120

140

160

(a) 2D image – monostatic – linear

Cro

ss−

Ran

ge (

cm)

Range (cm)


100 200 300 400 500 600

20

40

60

80

100

120

140

160

(b) 2D image – monostatic – log

Cro

ss−

Ran

ge (

cm)

Range (cm)


100 200 300 400 500 600

20

40

60

80

100

120

140

160

(c) 2D image – bistatic – linear

Cro

ss−

Ran

ge (

cm)

Range (cm)


100 200 300 400 500 600

20

40

60

80

100

120

140

160

(d) 2D image – bistatic – log

Figure 4.14: Imaging result for one plaster board wall

36

0 100 200 300 400 500 600−30

−25

−20

−15

−10

−5

0

y [Range (cm)]

I(y)

(dB

)



0 20 40 60 80 100 120 140 160−30

−25

−20

−15

−10

−5

0


I(x)

(dB

)



0 100 200 300 400 500 600−30

−25

−20

−15

−10

−5

0

y [Range (cm)]

I(y)

(dB

)



0 20 40 60 80 100 120 140 160−30

−25

−20

−15

−10

−5

0


I(x)

(dB

)




0 100 200 300 400 500 600−30

−25

−20

−15

−10

−5

0

y [Range (cm)]

I(y)

(dB

)



0 20 40 60 80 100 120−30

−25

−20

−15

−10

−5

0


I(x)

(dB

)



0 100 200 300 400 500 600−30

−25

−20

−15

−10

−5

0

y [Range (cm)]I(

y)

(dB

)



0 20 40 60 80 100 120 140 160−30

−25

−20

−15

−10

−5

0


I(x)

(dB

)




37

It is noted that the static horn was located at x = 80cm which was the middle of the SA. It

could be observed from the above figures that:

• The single wall appears in the results for both configurations. However, only part of the

wall which was directly in front of the static horn is resolved in the 2-D image. This result

matches the experimental result with the pin-up board and could again be explained by

using the radiation pattern of the horn antennas.

• The objects were physically located at (128cm, 333cm) and (59cm, 203cm). However,

the peak locations for pseudo-monostatic configuration are (127cm, 327cm) and (56cm,

196cm), and for bistatic configuration are (127cm, 327cm) and (66cm, 196cm). There

is a difference between the real locations and the positions of object as seen in imaging

result. They are relatively close or in other words, the imaging result could provide a

rough estimation of the real location of the objects.

• The resolutions in both range and cross range directions match with previous experimental

results.

• The presence of the wall increases the level of sidelobes in both range and cross range

profiles. The down-range sidelobes of the wall could be seen in the logarithmic 2-D image

in Figure 4.14.

• There is a confusing near field pattern close to the SA for both configurations. The

processing steps were used under an assumption that the target range is of far field as

seen by the SA. However, for the effective aperture size D = 1.6m and the wavelength

λ = 10cm (f = 3GHz), the boundary range between far field and near field is:

Ro = D2/λ = 25.6m

which is much higher than the size of the region to image. Near-field artifact or cross-talk

between horn antennas could potentially be the reason for this pattern but it has not

been explained up to this stage of the project.

4.4.5 Two plaster boards

The experimental results for the double wall formed by two plaster boards are shown in Figures

4.17, 4.18 and 4.18. For the bistatic configuration, the static horn was located at x = 80cm

which was the middle of the SA.

The significant aspects observed from the results are as follows:

• The objects stay within 3dB region from the imaging peaks, as discussed for previous

experiments.

38

• Two layers of the wall are resolved in the final image and the studs can be located in the

result of monostatic configuration. The studs are at the imaging holes within the wall as

seen in Figure 4.17(b).

• The presence of the wall introduces an increase in the sidelobe level of both range and

cross range profiles. The resolutions in both axes are comparable to previous simulation

and experimental results.

• Unknown near field pattern again appears in the image for the pseudo-monostatic con-

figuration.

Cro

ss−

Ran

ge (

cm)

Range (cm)


100 200 300 400 500 600

20

40

60

80

100

120

140

160

(a) 2D image – monostatic – linear

Cro

ss−

Ran

ge (

cm)

Range (cm)


100 200 300 400 500 600

20

40

60

80

100

120

140

160

(b) 2D image – monostatic – log

Cro

ss−

Ran

ge (

cm)

Range (cm)


100 200 300 400 500 600

20

40

60

80

100

120

140

160

(c) 2D image – bistatic – linear

Cro

ss−

Ran

ge (

cm)

Range (cm)


100 200 300 400 500 600

20

40

60

80

100

120

140

160

(d) 2D image – bistatic – log

Figure 4.17: Imaging result for two plaster boards wall

39

0 100 200 300−20

−18

−16

−14

−12

−10

−8

−6

−4

−2

0

y [Range (cm)]

I(y) (

dB)


0 50 100 150−20

−18

−16

−14

−12

−10

−8

−6

−4

−2

0


I(x) (

dB)


(a) Object 1

0 100 200 300 400−20

−18

−16

−14

−12

−10

−8

−6

−4

−2

0

y [Range (cm)]

I(y) (

dB)


0 50 100 150 200−20

−18

−16

−14

−12

−10

−8

−6

−4

−2

0


I(x) (

dB)


(b) Object 2


0 100 200 300−20

−18

−16

−14

−12

−10

−8

−6

−4

−2

0

y [Range (cm)]

I(y) (

dB)


0 50 100 150−20

−18

−16

−14

−12

−10

−8

−6

−4

−2

0


I(x) (

dB)


(a) Object 1

0 100 200 300 400−20

−18

−16

−14

−12

−10

−8

−6

−4

−2

0

y [Range (cm)]I(y

) (dB

)


0 50 100 150 200−20

−18

−16

−14

−12

−10

−8

−6

−4

−2

0


I(x) (

dB)


(b) Object 2


40

4.5 Imaging result for a real office wall

An office wall was used for the experiments as an attempt to test the imaging radar for a real

environment. The wall is made of plaster boards but its internal structure was left unknown.

The arrangement of the experiment is shown in Figure 4.20.

(a) SAR and wall (b) RF targets

Figure 4.20: Experimental set-up for a real office wall

The 2-D images of various configurations of the SA are shown in Figure 4.21. The locations

of the static horn antenna in the experiments are shown in the captions. The result presented

match with the previous experimental results about the wall being partly resolved for bistatic

configuration. The first object (closer to the SA) were clearly resolved in all images but the

second object could not be clearly seen due the noise and clusters. The blurry pattern behind

the second object was assumed to be the image of the second wall of the office since its location

matches with the actual location of the wall.

41

Cro

ss−

Ran

ge (

cm)

Range (cm)

2−D log image, objects are at (86,189) and (143,313)

50 100 150 200 250 300 350 400

20

40

60

80

100

120

140

160

(a) Bistatic (static horn at 0cm)

Cro

ss−

Ran

ge (

cm)

Range (cm)


50 100 150 200 250 300 350 400

20

40

60

80

100

120

140

160

(b) Bistatic (static horn at 80cm)

Cro

ss−

Ran

ge (

cm)

Range (cm)


50 100 150 200 250 300 350 400

20

40

60

80

100

120

140

160

(c) Bistatic (static horn at 162cm)

Cro

ss−

Ran

ge (

cm)

Range (cm)

2−D logarithmic image, objects are at (86,189) and (143,313)

0 50 100 150 200 250 300 350 400

20

40

60

80

100

120

140

160

(d) Pseudo-monostatic

Figure 4.21: Imaging result for a real office wall

In an attempt to combine various experimental results using different configurations, the

image of the region of interest was extracted as seen in Figures 4.22 and 4.23. The individual

2-D images of the region using the bistatic configurations as seen above were combined and

superimposed by adding or multiplying. These operations are the equivalence of the cross-

correlation operation between the images. By doing so, the quality of the images increased

which can be reflected in both 2-D images and range and cross range profiles. The range and

cross range resolutions of the images formed by combining multiple images are much better

compared to the original individual images.

42

Cro

ss−

Ran

ge (

cm)

Range (cm)

bistatic combination, objects are at (86,189) and (143,313)

50 100 150 200 250 300 350 400

20

40

60

80

100

120

140

160

(a) 2D image

0 50 100 150 200 250 300 350 400−20

−18

−16

−14

−12

−10

−8

−6

−4

−2

0

y [Range (cm)]

I(y)

(dB

)


(b) Range profile

0 20 40 60 80 100 120 140 160−30

−25

−20

−15

−10

−5

0


I(x)

(dB

)



Figure 4.22: Combine the results by adding

Cro

ss−

Ran

ge (

cm)

Range (cm)

bistatic combination, objects are at (86,189) and (143,313)

50 100 150 200 250 300 350 400

20

40

60

80

100

120

140

160

(a) 2D image

20 40 60 80 100 120 140 160 180 200 220−80

−70

−60

−50

−40

−30

−20

−10

0

y [Range (cm)]

I(y)

(dB

)


(b) Range profile

70 75 80 85 90 95 100 105 110−80

−70

−60

−50

−40

−30

−20

−10

0


I(x)

(dB

)



Figure 4.23: Combine the results by multiplying

43

4.6 Remarks

Various experiments using different wall materials were conducted and their results were anal-

ysed. The significant results from the experiments can be summarised as follows:

• Objects were resolved at correct locations in the final image.

• Down range and cross range resolutions were comparable to theoretical value and simu-

lation result. The down range resolution for both SA configurations was 10cm. The cross

range resolution for the pseudo-monostatic configuration was approximately 10cm while

its value for the bistatic configuration was 15cm.

• The wall was partly resolved in the result of the experiments using bistatic configuration

for the SA. Full wall appeared in the result for pseudo-monostatic case.

• The processing technique and propagation model performed well for single and double

layer walls.

• There was a confusing near-field pattern close to the SA.

44

Chapter 5

Project Management

This chapter will give a brief look at some management aspects of the project, which include

schedule management, risk mitigation and budget review.

5.1 Work Plan and Schedule Revisit

The proposed work has been successfully completed as planned. There is no significant change

to the Gantt chart during the execution phase of the project. Previous versions of the project

schedule could be found in [10],[11]. There was a delay in the initial imaging experiments in

Semester A due to the late arrival of the horn antennas. The schedule was adjusted accordingly

and time delay was compensated by the work during the mid-year break. One optional task

was completed which is conducting the experiment with various wall materials. The up-to-date

Gantt chart of the project is shown in Figure 5.1.

Table 5.1 shows the status of planned tasks up to this stage of the project. All experiments

in the chamber and real environment were conducted and met the schedule.

The tasks were allocated to team member based on the availability and the experience of

members. Weekly informal and formal meetings were held for planning and reporting progress.

More on initial group role allocation and auditing plan for this project can be found in [10].

Due to the main focus of the second stage of the project was software and signal processing,

task and group roles were slightly modified. The experiments were conducted by the whole

team and tasks for software development and result analysis were equally divided between

team members.

45

Figure 5.1: Gantt Chart

46

Planned Task Status

Proposal Complete

System design Complete

System simulation Complete

1-D imaging Complete

2-D imaging in anechoic chamber Complete

2-D imaging in controlled environments Complete

System testing and validation Complete

Experiment with various wall materials Complete

3-D imaging Incomplete

Table 5.1: Project progress

5.2 Risk Management

5.2.1 Risk occurred

5.2.1.1 Delay in material procurement and construction

In Semester A, horn antennas were chosen for the configuration of SA and it was decided that

two horns would be borrowed from DSTO. However, there was a short delay in getting the

antennas delivered which resulted in an adjustment in the project schedule.

In Semester B, a wall formed of plaster boards was built in an attempt to test the system

with a real wall. There was a long delay (about one week) for the plaster boards to be ordered

and delivered to campus. Due to various reasons, the wall construction using these plaster

boards was also delayed for about one week. However, the delays were quickly compensated

since the project was ahead of schedule.

5.2.1.2 Subversion blackout

Since the project dealt with large amount of data and programs, it was decided in planning phase

that Electrical and Electronic Engineering (EEE) School’s Subversion Control (SVN) reposi-

tory would be used for managing and storing data. While it provided flexibility, SVN posed a

great risk in the case that it was corrupted or data was lost or inaccessible. It did happen twice

over two weekends (end of week 10 and 11, Semester A) when there was unexpected power

outage in Engineering South building, where the SVN server is housed. The processing of data

was therefore terminated until server was manually rebooted in the following Mondays. The

solution for the following stage was to have working copy stored offline to be accessed if needed.

47

5.2.1.3 Anechoic chamber and VNA unavailable

Since the access of the anechoic chamber and the VNA is managed by booking, it was booked

out and could not be accessed for some particular days. This caused the delay for conducting

experiments which can only be done when both lab and instrument are available. This risk did

cause a short delay for the project, but did not affect the overall progress.

5.2.1.4 Lack of technical knowledge

Due to the inexperience of team members with reflection measurement calibration and radar

imaging technique, handling related challenges was time-consuming. This caused the project to

stay behind schedule most of the time in semester A. However, when the problem was solved,

delay could quickly be compensated and tasks were back on track.

5.3 Budget review

Table 5.2 lists all up-to-date expenses for this project. All numerical figures are finalised and

there will be no further purchases being made for this project. The real figure is slightly

lower than proposed cost since most RF components and instrument were borrowed and not

externally purchased.

Item Cost Note

SAR mounting - Built by workshop

N-type cable x 2 - Borrowed from phased array lab

VNA - Borrowed from the anechoic chamber

Horn antennas - Borrowed from DSTO

SMA male - N female adaptor x 4 - Borrowed from EEE labs

RF targets - Borrowed from the workshop

Wall construction $83.06 Material bought from Bunning

Exhibition printing $10 Estimate cost

Total Cost $93.06

Proposed budget Real cost Remaining budget

$290 $93.06 $500 - $93.06 = $406.94

Table 5.2: Budget review

48

Chapter 6

Conclusion

6.1 Future Work

The work done for this project has laid down the foundation so that extension or future work

can be performed:

1. Automatic 2D imaging

The experiments were manually conducted by sliding the horn antennas across the SAR.

The data from each measurement is acquired and stored for offline processing. The

process for getting image of ROI is consequently slow, although it does not take long

to generate the image once data is collected. The followings could be used to enable

automatic imaging using the same system and configuration:

• Stepper motors to quickly and automatically move the horn antennas along the SAR.

• Live data acquisition and signal processing by either remote controlling the VNA

by MATLAB using Local Area Network (LAN) or General Purpose Interface Bus

(GPIB), or using dedicated hardware and signal processing unit.

2. Setting up theory for near-field Synthetic Aperture Radar imaging

The experimental work has proved the difficulty of using far-field theory to explain beam-

forming artifacts in the final image. The theoretical background is needed to completely

explain the experiment result, which includes the disturbance in the image close to the

synthetic aperture or the presence of repeating pattern in the image of the empty room.

3. 3D imaging

In practical situation, it is not often useful to only see one 2-D slide of the scene. The

radar being able to generate a 3D image of objects behind the wall would be ideal for

many reasons. The following work can be done to achieve such requirement:

49

• Vary the height of current SAR to capture multiple 2D slides and reconstruct 3D

scene using 2D results.

• Change the focusing delay model to deal with third dimension (elevation direction)

and redesign mechanical structure for a two dimensional SA.

6.2 Project Outcomes

2-D image of the region of interest behind a wall has been successfully generated. The pseudo-

monostatic configuration results in better cross range resolution compared to bistatic case.

Experiments were conducted for various wall materials (pin-up board, plaster wall and office

wall) and the results prove the feasibility of through the wall imaging application using a

Synthetic Aperture Radar. The designed radar system is simple and of low cost, which can

be used for research application. The outcome of this project serves as a foundation for the

implementation of a more complex through-wall radar system.

50

Bibliography

[1] E. J. Baranoski, “Through-wall imaging: Historical perspective and future directions,”

Journal of the Franklin Institute, vol. 345, no. 6, pp. 556 – 569, 2008.

[2] A. Braga and C. Gentile, “An ultra-wideband radar system for through-the-wall imaging

using a mobile robot,” in Communications, 2009. ICC ’09. IEEE International Conference

on, pp. 1 –6, june 2009.

[3] F. Ahmad, M. Amin, and S. Kassam, “Synthetic aperture beamformer for imaging through

a dielectric wall,” Aerospace and Electronic Systems, IEEE Transactions on, vol. 41,

pp. 271 – 283, jan. 2005.

[4] M. Amin and F. Ahmad, “Wideband synthetic aperture beamforming for through-the-

wall imaging [lecture notes],” Signal Processing Magazine, IEEE, vol. 25, pp. 110 –113,

july 2008.

[5] S. Kidera, T. Sakamoto, and T. Sato, “A high-resolution 3-d imaging algorithm with

linear array antennas for uwb pulse radar systems,” in Antennas and Propagation Society

International Symposium 2006, IEEE, pp. 1057 –1060, july 2006.

[6] J. Zhu, Y. Hong, and L. Tao, “3d imaging algorithm and implement for through-wall

synthetic aperture radar,” in Circuits and Systems, 2009. MWSCAS ’09. 52nd IEEE In-

ternational Midwest Symposium on, pp. 561 –564, aug. 2009.

[7] F. Ahmad, Y. Zhang, and M. Amin, “Three-dimensional wideband beamforming for imag-

ing through a single wall,” Geoscience and Remote Sensing Letters, IEEE, vol. 5, pp. 176

–179, april 2008.

[8] W. M. Brown and L. J. Porcello, “An introduction to synthetic-aperture radar,” Spectrum,

IEEE, vol. 6, pp. 52 –62, sept. 1969.

[9] A. Currie, “Synthetic aperture radar,” Electronics Communication Engineering Journal,

vol. 3, pp. 159 –170, aug 1991.

[10] T. Bui and J. Rabig, “Stage 1 progress report - project: Through-the-wall imaging radar,”

tech. rep., Adelaide University, 2011.

51

[11] T. Bui, “Stage 2 progress report - project: Through-the-wall imaging radar,” tech. rep.,

Adelaide University, 2011.

52

Appendix A

MATLAB Code

This appendix lists out sample MATLAB programs used to process collected data and generate

the 2-D image. It also includes a segment of the typical measurement result collected using the

VNA.

Listing A.1: Sample measurement result

! Agilent Technologies , N5230A , US43500294 , A . 0 4 . 2 5

! Agilent N5230A : A . 0 4 . 2 5

! Date : Thursday , September 15 , 2011 1 5 : 4 8 : 1 3

! Correction : S11 ( Full 2 Port SOLT , 1 , 2 ) S21 ( Full 2 Port SOLT , 1 , 2 ) S12 ( Full 2 Port SOLT , 1 , 2 ) ←֓

S22 ( Full 2 Port SOLT , 1 , 2 )

! S2P File : Measurements : S11 , S21 , S12 , S22 :

# Hz S dB R 50

2500000000 −7.430793 e+000 −1.600484 e+002 −3.742124 e+001 1.115331 e+002 −3.746042 e+001 ←֓

1.119385 e+002 −6.741900 e+000 1.741262 e+002

2510000000 −9.430097 e+000 −1.599856 e+002 −3.682345 e+001 9.019662 e+001 −3.680711 e+001 ←֓

8.982121 e+001 −5.338504 e+000 −1.762050 e+002

2520000000 −7.807305 e+000 −1.694729 e+002 −3.502031 e+001 7.391974 e+001 −3.509335 e+001 ←֓

7.451751 e+001 −4.510386 e+000 −1.626250 e+002

2530000000 −8.758544 e+000 −1.584523 e+002 −3.319084 e+001 5.349775 e+001 −3.321054 e+001 ←֓

5.353482 e+001 −4.070266 e+000 −1.505258 e+002

2540000000 −9.448528 e+000 −1.741781 e+002 −3.262580 e+001 3.525972 e+001 −3.275987 e+001 ←֓

3.573086 e+001 −4.045329 e+000 −1.358550 e+002

2550000000 −8.199015 e+000 −1.650800 e+002 −3.151055 e+001 1.014828 e+001 −3.151619 e+001 ←֓

1.069734 e+001 −4.165150 e+000 −1.226444 e+002

2560000000 −1.054701 e+001 −1.651589 e+002 −3.112403 e+001 −6.580334 e+000 −3.128778 e+001 ←֓

−6.677758 e+000 −4.720467 e+000 −1.096675 e+002

2570000000 −8.813895 e+000 −1.712190 e+002 −3.048989 e+001 −3.088564 e+001 −3.044874 e+001 ←֓

−3.038239 e+001 −5.575526 e+000 −9.557133 e+001

2580000000 −9.635010 e+000 −1.571554 e+002 −3.061926 e+001 −5.116904 e+001 −3.077199 e+001 ←֓

−5.148961 e+001 −7.355277 e+000 −8.485722 e+001

2590000000 −1.014102 e+001 −1.730694 e+002 −3.013548 e+001 −6.606699 e+001 −3.009271 e+001 ←֓

−6.575909 e+001 −1.008304 e+001 −7.305842 e+001

2600000000 −8.658289 e+000 −1.612389 e+002 −2.969870 e+001 −9.283371 e+001 −2.979784 e+001 ←֓

−9.288857 e+001 −1.628804 e+001 −6.644978 e+001

. . .

# The remaining was deliberately deleted !

53

Listing A.2: Calibration using linear regression

f u n c t i o n p = calibration ( name , d )

% d i s a vector o f d i s t a n c e s between antennas

% name i s the s t a r t i n g s t r i n g o f the c a l i b r a t i o n data f i l e s

% p i s a 1x2 vector conta i n i ng the system delay p (2) and the speed o f

% wave i n the a i r gap 1/p (1)

len = l ength ( d ) ;

delays = z e r o s (1 , len ) ;

f o r i=1: len

fname = strcat ( name , num2str ( d ( i ) ) , ' . s2p ' ) ;

% open f i l e

fid = fopen ( fname , ' r ' ) ;

% read data

data = textscan ( fid , '%f%f%f%f%f%f%f%f%f ' , ' Header l i nes ' , 6 ) ;

f c l o s e ( fid ) ;

% e x t r a c t data

freq = data {1} ;

S21_magdB = data {4} ;

S21_phaseDeg = data {5} ;

S21 = db2mag ( S21_magdB ) . ∗ exp (1 i∗ S21_phaseDeg∗ p i /180) ;

h_d = i f f t ( S21 ) ;

fs = max( freq ) − min ( freq ) ;

time = ( 1 : l ength ( h_d ) ) /fs ;

h_abs = abs ( h_d ) ;

[ pks , locs ] = findpeaks ( h_abs , ' s o r t s t r ' , ' descend ' ) ;

delays ( i ) = time ( locs (1) ) ;

end

f i g u r e , p l o t ( d /100 , delays , ' ∗ r ' ) ;

xlim ( [ 0 . 9 ∗ min ( d ) /100 1 . 1∗max( d ) /100 ] )

ylim ( [ 0 , 1 . 1∗max( delays ) ] ) , hold on , g r i d on ;

x l a b e l ( ' Distance between antennas (m) ' )

y l a b e l ( ' Delay with no c a l i b r a t i o n ( s ) ' )

t i t l e ( ' Delay vs . Separ at i on ( September 26 th ) ' )

p = p o l y f i t ( d /100 , delays , 1 ) ;

delays_true = p (1) ∗d /100 + p (2) ;

p l o t ( d /100 , delays_true , '−ob ' )

str1 = s p r i n t f ( ' F i t ted data : delay = %.2d∗ d i s t a n c e + %.2d ' , p (1) , p (2) ) ;

l egend ( ' Co l l ec ted data ' , str1 , ' l o c a t i o n ' , ' South ' )

% r e g r e s s i o n c o e f f i c i e n t

r = c o r r c o e f ( d /100 , delays ) ;

t ext (1 , 0 . 25 e−8, s p r i n t f ( ' C o r r e l a t i o n c o e f f i c i e n t R = %.4 f ' , r ( 2 , 1 ) ) )

r e tur n

Listing A.3: Sample image processing program for an empty room

c l e a r a l l ;

c l o s e a l l ;

54

c l c ;

%% perform c a l i b r a t i o n

d = [ 53 93 137 1 8 6 ] ;

p1 = calibration ( ' S c a l ' , d ) ;

d = ( 0 : 4 : 1 4 4 ) ;

d_len = l ength ( d ) ;

c = 3e8 ;

N = 151 ;

freq = z e r o s (1 , N ) ;

H = z e r o s ( d_len , N ) ;

h = z e r o s ( d_len , N ) ;

f o r i = 1 : d_len

fname = strcat ( ' Se2 ' , num2str ( d ( i ) ) , ' . s2p ' ) ;

% open f i l e

fid = fopen ( fname , ' r ' ) ;

% read data

data = textscan ( fid , '%f %f %f %f %f %f %f %f %f ' , ' Header l i nes ' , 6 ) ;

f c l o s e ( fid ) ;

% e x t r a c t data

freq = data {1} ;

S21_magdB = data {4} ;

S21_phaseDeg = data {5} ;

S21 = db2mag ( S21_magdB ) . ∗ exp (1 i∗ S21_phaseDeg∗ p i /180) ;

S21_cal = S21 . ∗ exp (1 i∗2∗ p i ∗freq∗p1 (2) ) ;

h ( i , : ) = i f f t ( S21_cal ) ;

H ( i , : ) = S21_cal ;

fs = max( freq ) − min ( freq ) ;

end

%% 2D imaging

% dimension o f area i n i n t e r e s t

width = 1 . 6 ;

len = 6 ;

w = 1 : width ∗100;

l = 1 : len ∗100;

N_w = l ength ( w ) ;

N_l = l ength ( l ) ;

%% Frequency domain techn i que

pixels_freq = z e r o s ( N_w , N_l , N ) ;

f o r i = 1 : N_w ;

f o r j = 1 : N_l

di sp ( [ '@ row ' num2str ( i ) ' c o l ' num2str ( j ) ] ) ;

% d i s t a n c e i s the d i s t a n c e from horn1 to horn 2 v i a p i x e l ( i , j )

distance = 1/100 ∗ ( s q r t ( ( i−d−16) .ˆ2+j ˆ2) + s q r t ( ( i−d ) .ˆ2+j ˆ2) ) ;

sum1 = z e r o s (1 , N ) ;

f o r k = 1 : d_len

sum1 = sum1 + H ( k , : ) . ∗ exp (1 i∗2∗ p i ∗freq . ' ∗ distance ( k ) /c ) ;

end

pixels_freq ( i , j , : ) = sum1 ;

end

end

I = abs (sum( pixels_freq ( ) , 3 ) ) ;

%% p l o t the r e s u l t

55

% l i n e a r s c a l e

f i g u r e , imagesc ( I ) , colormap ( j e t )

y l a b e l ( ' Cross−Range (cm) ' ) , x l a b e l ( ' Range (cm) ' )

t i t l e ( '2−D image , empty room ' )

% l og s c a l e

f i g u r e , imagesc ( mag2db ( I/max(max( I ) ) ) ) , colormap ( j e t )

y l a b e l ( ' Cross−Range (cm) ' ) , x l a b e l ( ' Range (cm) ' )

t i t l e ( '2−D image , empty room , l og s c a l e ' )

% range at x = 80

f i g u r e , p l o t ( mag2db ( I ( 8 0 , : ) /max( I ( 8 0 , : ) ) ) , ' Linewidth ' , 2 ) ;

x l a b e l ( ' y [ Range (cm) ] ' ) ; y l a b e l ( ' I ( y) (dB) ' )

t i t l e ( ' Range p r o f i l e at x = 80 cm ' )

g r i d on ; ylim ([−30 0 ] )

56

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