reconstruction of reference signal for dvb-s based …©2013 engineering and technology publishing....

Reconstruction of Reference Signal for DVB-S

Based Passive Radar Systems

Lu Hongchao, Liu Bing, Guo Hongqi, and Huang Biao Military Representative Office of PLA in 209

th Institute, Chengdu, Sichuan, P. R. China

Email: [email protected]

Abstract—Direct broadcasting satellites (DBS) are good

opportunity illuminator for passive radar system. This

paper presents a method for reception, decoding and

reconstruction of DVB-S transmitting signal for the purpose

of using it in passive radar systems as a reference signal.

Therefore, this paper studies the performance of DBS as the

opportunity illuminators for passive radar. The simulation

results demonstrate that the recreated reference signal has a

high similarity with the transmitted signal, which can act as

a perfectly reconstructed and error-free match signal for

the following 2D Cross-correlation processing.

Index Terms—passive radar, DVB-S, DBS, reference signal

reconstruction

I. INTRODUCTION

Passive radar based on opportunity illuminators (such

as Global Positioning System (GPS) [1], Television

stations (TV) [2], Frequency Modulation (FM) radio

broadcasts [3], Global System of Mobile communication

(GSM) [4]) is an important research topic in designing

new-style radar systems. And they have numerous

advantages [5] such as low-cost, increased survivability

and robustness. In a military context, passive radar

systems bring frequency diversity, new electronic

countermeasures challenges, and thus are difficult to

locate. What is more, they can offer enhanced detection of

low-observable targets [6].

Compared with the opportunity illuminators on the

ground, the opportunity illuminators in space such as

direct broadcasting satellites (DBS) and GPS have

advantages such as wider-spread in space (which means

bigger observation angle), broader beam coverage.

Further, we can receive more than one satellite signal

simultaneously. However, the non-geostationary satellite

as opportunity illuminators exist problems such as system

configuration time-varying, Doppler frequency shift

caused by the movement of the transmitter, as well as the

irradiation time on the fixed area is short. DBS in

geostationary orbit overcome these shortcomings, and the

ambiguity function of DBS signal waveform has a

Manuscript received May 17, 2013; revised August 2, 2013

thumbtack, you can ensure a good range resolution and

velocity resolution [7].

In passive radar systems, a reference signal is needed

for echo receiving. The reference signal can be obtained

by a separate reference channel with antenna pointing

toward the transmitter. In this approach, however, the

reference signal is noisy and multipath clutter polluted,

which leads to depravation of the obtained results. As we

know, high quality reference signal acquisition is a key

problem for passive radar systems. In order to obtain more

pure reference signal, Signal reconstruction method based

on the fact that digital transmission schemes are more

robust to noise than analog modulations is raised. The

reference signal reconstruction for Digital Audio

Broadcasting (DAB) and Digital Video Broadcasting-

Terrestrial (DVB-T) based passive radar have been

reported [8], [9], where the former emphasizes on utilizing

a method of target detection by correlating a target signal

with the reconstructed reference signal, and the latter aims

to develop a method enabling decoding of the signal using

an universal receiver not only dedicated for DVB-T

standard. The reference signal reconstruction for China

Mobile Multimedia Broadcasting (CMMB) and Digital

Terrestrial Multimedia Broadcasting (DTMB) based

passive radar have been studied by Wuhan University [10,

11]. However, to the authors’ knowledge, the reports

about the research on the reconstruction of reference

signal for DBS-based passive radar haven’t been reported

at present.

There are 8 DBS which operate on Ku frequency band

in China nowadays [12]. Six of those satellites operate on

Digital Video Broadcasting-Satellite (DVB-S) standard.

In this paper, an effective approach is represented to

reconstruct the reference signal, here we focus on the

problems associated with the decoding and reconstructing

of the DVB-S signal, and verification of the

reconstruction of DVB-S reference signal. The rest of the

paper is organized as follows. The paper is organized as

follows. Section II studies the DVB-S standard. Section

Ⅲ present the reconstruction process. SectionⅣ verify

reconstructed reference signal. Section Ⅴ provide

conclusion and future work.

International Journal of Signal Processing Systems Vol. 1, No. 1 June 2013

©2013 Engineering and Technology Publishing 116doi: 10.12720/ijsps.1.1.116-120

app:ds:standard

II. DVB-S STARDARD

DVB-S standard based DBS signals is mainly

composed by two parts of the source coding and satellite

channel adapting [13]. Wherein the source coding uses the

MPEG-2 coding, first audio and video data of a television

program are multiplexed, and then a plurality of digital

video stream to be transmitted multiplexed. Satellite

channel adapter includes transport multiplex adaptation

and randomization for energy dispersal, channel coding,

baseband shaping and QPSK modulation. In order to

comply with ITU Radio Regulations and to ensure

adequate binary transitions, the data of the input MEPG-2

multiplex is randomized. Channel coding is the theoretical

basis for that the signal reconstruction method can remove

the clutter and noise for DBS signal, which including

outer coding, convolutional interleaving, and inner coding.

Prior to modulation, the signals are square root raised

cosine filtered, the roll-off factor is 0.35. DVB-S signal

transmission system functional block diagram is shown in

Fig. 1.

MUX adaptation

&Energy

dispersal

Video coder

Audio coder

Data coder

Pro

gra

mm

e

MU

X

Tra

nsp

ort

M

UX

Conv. Inter-leaver

Outer coder

Inner coder

Baseband shaping

QPSK modulator

Service components

1

2

n

…

Services

MPEG-2Source coding and multiplexing Satellite channel adapter

to the RF satellite channel

Channel coding

Figure 1. Functional block diagram of DVB-S transmission system.

The framing organization is based on the input packet

structure, as shown in Fig. 2.

Sync1Byte

187 Byte

（a）MPEG-2 transport MUX packet

Sync1

（b）Randomized transport packets; Sync bytes and randomized sequence R

R187Byte

R187Byte

R187Byte

PRBS period =1503Byte

（c）RS（204,188，T=8）error protected packet

Sync1

204Byte

（d）Interleaved frames; interleaving depth I=12

Sync 1 = not randomized complemented sync byte

Sync n = not randomized sync byte, n=2,3,4 …… 8

187 Byte

203 Byte

or Sync n

Sync1or Sync n

Sync1or Sync n

Sync1or Sync n

203 Byte

RS(204,188,8)

Sync 2 Sync 2 Sync1

Figure 2. Framing structure

Out coding use Reed-Solomon RS (204,188, T=8)

shortened code, from the original RS (255,239, T=8) code.

RS coding is applied to each randomized transport packet

(188bytes) including the packet sync byte to generate an

error protected packet. After RS (204,188, T=8) coding,

the length of packet become 204bytes. The shortened RS

code may be implemented by adding 51bytes, all set to

zero, before the information bytes at the input of a RS

(255,239) encoder. After RS coding procedure these null

bytes shall be discarded. Code generator polynomial of

RS (255,239, T=8) is

0 1 15g x x x x

(1)

where =02H , H means HEX.

To prevent burst channel errors, convolutional

interleaving with depth I=12 is applied to the error

protected packets. This results in an interleaved frame,

preserving the periodicity of 204 bytes. The conceptual

diagram of the convolutional interleaver and de-

interleaver is shown in Fig. 3.

The interleaver is composed of I=12 branches,

cyclically connected to the input byte-stream by the input

switch. Each branch is a First-In, First-Out (FIFO) shift

register, with depth (M j) cells, where M=17=N/I,

N=204= error protected frame length, I=12= interleaving

depth, j=branch index. The cells of the FIFO shall contain

1 byte, and the input and output switches shall be

synchronized. For synchronization purposes, the sync

bytes and the inverted sync bytes shall be always routed in

the branch ‘0’ of the interleaver.

17=M

17X2

17X3

17X11

1 1

2 2

3 3

4 4

11 11= I-1

1 byte per position

Interleaver I=12

FIFO shift register

Sync word route17X11

17X3

11

8

De-interleaver I=12

17X2

17=M

11

1010

9

8

9

1 1

1 byte per position

Sync word route

Figure 3. Conceptual diagram of the convolutional interleaver and de-interleaver.

Inner coding use punctured convolutional codes, based

on a rate 1/2 convolutional code with constraint length

K=7. DVB-S standard allow convolutional coding with

code rates of 1/2, 2/3, 3/4, 5/6 and 7/8, as given in Table

Ⅰ.

TABLE I. PUNCTURED CODE DEFINITION.

Original code Code rates

K G1

(x)

G2

(y) 1/2 2/3 3/4 5/6 7/8

7 171oct 133oct

X:1

Y:1

I=X1

Q=Y1

X:10

Y:10

I=X1Y2Y3

Q=Y1X3Y4

X:101

Y:110

I=X1Y2

Q=Y1X3

X:10101

Y:11010

I=X1Y2Y4

Q=Y1X3X5

X:1000101

Y:1111010

I=X1Y2Y4Y6

Q=Y1Y3X5X7

Note：1= transmitted bit；0= non transmitted bit

The system which adapt DVB-S standard shall employ

conventional Gray-coded QPSK modulation with absolute

mapping. In order to suppress the modulated signal out-

of-band radiation, I and Q (mathematically represented by


©2013 Engineering and Technology Publishing 117

a succession of Dirac delta functions spaced by the

symbol duration Ts) signals are square root raised cosine

filtered. The frequency domain expression of the square

root of raised cosine filters is

1/ 2

1 , (1 )

1 1{ sin [ ]}

2 2 2( )

(1 ) (1 )

0 (1 )

N

N

N

N N

N

f f

f f

fH f

f f f

f f

，

，

(2)

where, S1 2Nf T is Nyquist frequency, and 0.35 is

the roll-off coefficient.

III. RECONSTRUCTION METHOD

A. Reconstruction Process

The basic idea of the signal reconstruction is recover

the symbols of transmitted signal from the local received

direct wave signal by demodulation, according to the

special signal structure, the signal coding and modulation

method. Then one can obtain pure direct reference signal

by re-coding and re-modulation to the solved transmitted

symbols.

Direct wave signal reconstruction of passive radar

system based on DBS is according to the DVB-S signal

modulation and demodulation process, to recover the

transmitter signal from the received direct wave as

accurately as possible. The basic process of signal

reconstruction is shown in Fig. 4.

Sync decoder

Reconstructed direct wave

Received direct wave Carrier

recoveryChannel decoding

Channel coding

Baseband shaping

QPSKmodulation

Signal re-modulationSignal de-modulation

Figure 4. Direct wave reconstruction process

Received direct wave from reference signal receiving

channel after the carrier recovery, synchronization, and

channel decoding processing restore the binary bits stream

of a possible for low bit error rate, then after channel

coding, the base band forming and the QPSK modulation

to complete the reconstruction of direct wave.

B. Key Technology of DVB-S Signal Reconstruction

DVB-S signal reconstruction shall restore the binary

bits stream of transmitted signal from the received direct

wave. Demodulation of the DVB-S signal is the inverse of

the modulation process. The purpose of reconstruct the

direct wave is to remove the noise and other interference

in the received direct wave, without the need to

demodulating the television program. Therefore the signal

demodulation only needs to solve channel coding, without

the need to solve the energy randomization and program

multiplex. DVB-S signal demodulation flow chart is

shown in Fig. 5.

QPSKdemodulation

Received direct signal Matched

filterInner

decoder

Carrier &clock recovery

De-inter-leaver

Sync decoder

Outer decoder

Transmitted bits stream

Clock &Sync generator code rate control

I

Q

Figure 5. DVB-S signal demodulation flow chart

Synchronization is the key process of signal

reconstruction, directly affects the quality of the reference

signal. The main purpose of synchronization is obtaining

the starting point of the signal frame, to estimate the

sampling error introduced in the mixing process in the

frequency deviation and the sampling process, and to

compensate for it.

As described in Fig. 2, each frame of DVB-S signal

includes a synchronization byte, 47H. In order to identify

the starting point of frame group, the first synchronization

bytes of each frame group is inverted bite-by-bite, become

B8H. Other seven frame synchronization bytes remain

unchanged. The use of a windowed peak detection method

can capture the position of the synchronizing signal, see

equation (3)

*syncn N

synci n

R t s i s i N

,1 2n N (3)

Wherein, n corresponding to the number of the

sampling point, syncN responding the length of the sync

byte, s i is the sampled DVB-S signal, N is the length

of a DVB-S signal frame group. In order to utilize two full

frame group synchronization signals, take the sliding

length to 2N.

There is phase ambiguity in the decoding of

punctured convolutional code. After completion of the

synchronization signal, the phase ambiguity problem can

be solved by comparing the difference of the frame

synchronization bytes and the frame group

synchronization byte between the decoded bits stream and

the actual.

IV. RECONSTRUCTED SIGNAL PERFORMANCE

ANALYSIS

A. BER of Channel Decoding

Signal reconstruction need obtain the transmitted bit

stream by signal demodulation and channel decoding.

Then reconstruct a pure direct wave by channel coding

and QPSK modulation according to the demodulated bits

stream. Visible, bit error rate (BER) of channel decoding

has a very important impact on the performance of the

reconstructed signal, only the low BER can ensure that the

reconstructed signal with the transmitted signal has a high

level of consistency. The quality of reconstructed signal is

certainly poor with high BER.

A simulation is made with 8 frame group data, each

code symbol is responded by 2bits data, and assuming the

noise is additive white Gaussian noise. The BER, obtained



by simulation, to the signal to noise radio (SNR) is shown

in Fig. 6.

-5 -4 -3 -2 -1 0 1 210

-2

10-1

100

SNR of received direct wave/dB

BE

R

Figure 6. BER to the SNR of received direct wave

As can be seen in Fig. 6, when the SNR of received

direct wave is low (especially less than -3dB), BER is

high, about 50%. But when the SNR of received signal is

greater than -3dB, the BER of channel decoding is rapidly

reduced with the improvement of SNR, when the SNR of

received direct wave is high to 2dB, the BER can reached

the order of 10-2

. Because of the length of the simulation

data, when the SNR of received direct wave is greater

than 3dB, BER of channel decoding can reach zero, which

means able to fully demodulate the transmitted code

stream, and thus can achieve the accurate reconstruction

of the direct wave signal.

B. Output SNR

Since the transmitted bits stream is an intermediate

amount for signal reconstruction, not an end in need of

reference signal. BER of channel decoding have a

significant impact on the reconstructed signal

performance, but it is not an accurate measure of the

reconstructed signal performance. In order to better

measure of the reconstructed signal of the noise

suppression performance, we introduce the output SNR,

which is defined as follow

2210lg / ˆ

outSNR s i s i s i (4)

where s i and s i , respectively, represent the

transmitted signal and reconstructed signal.

Fig. 7 shows the output SNR of reconstructed direct

wave to the SNR of received direct wave, obtained by

simulation with the same simulation conditions as above.

-5 -4 -3 -2 -1 0 1 2 3 4 50

2

4

6

8

10

12

14

16

18


Outp

ut S

NR

/dB

Figure 7. Output SNR of reconstructed direct wave

As in Fig. 7, the output SNR of reconstructed direct

wave increase with the improvement of received direct

wave SNR. Especially when the SNR of received direct

wave is greater than 3dB, the output SNR of the signal

reconstruction tends to infinity, which means the noise is

removed. For the actual passive radar imaging system

based on DBS, the SNR of received direct wave is about

16dB, which means the BER of channel decoding can

approach zero and able to accurately reconstruct the direct

wave as reference signal.

C. NMSE of Reconstructed Signal

For passive radar imaging system, not only need the

reference signal have a high SNR, but also require the

waveform of the reference signal is consistency to the

transmitted signal. In this paper, the normalized mean

square error (NMSE) is utilized to measure the

consistency of time-domain waveform between the

reconstructed signal and the transmitted signal.

-4 -2 0 2 410

-2

10-1

100


NM

SE

/dB

Figure 8. NMSE of reconstructed signal

Fig. 8 shows the NMSE of reconstructed signal to the

SNR of received direct wave, obtained by simulation with

the same simulation conditions as above. As in Fig. 8, the

NMSE of reconstructed signal rapidly decrease with the

improvement of the SNR of received direct wave. When

the SNR of received direct wave is greater than 3dB, the

NMSE is approach to zero, indicating that the

reconstructed signal waveform is highly consistent with

the transmitted signal.

D. Cross Ambiguity Function

Whether the BER of channel decoding, the output SNR,

or NMSE of the reconstructed signal is a quantitative

indicator, which require the transmitted signal is known to

evaluate the performance of the reconstructed signal. But

this is unrealistic for the actual passive radar system.

Ambiguity function is an effective tool for radar signal

analysis and waveform designing [9]. It shows the

resolution, the ambiguity degrees, the measuring precision

and the clutter suppression ability of the given transmitted

waveform. The cross ambiguity function between the

reconstructed signal and the received signal can visually

check the quality of the reconstructed signal. Cross

ambiguity function is defined as

j2π*χ , e dˆ df

dt f s s t

(5)



where t represents time delay, and df represents Doppler

frequency.

Figure 9. Cross ambiguity function

Fig. 9 shows the cross ambiguity function result, where

the SNR of received direct wave is 15dB. A strong peak

appears obviously, which states clearly that the

reconstructed reference signal is highly similar with the

transmitted signal, while the low side-lobe illustrates the

noise of the reconstructed signal is less, and the purity is

high.

V. CONCLUSIONS

The signal reconstruction method is improved to be an

effective means of reducing the noise in passive radar

imaging system based on DVB-S. The current work is

limited, the signal reconstruction method still need to be

improved by real-life signal, but it provides the basis for

the further study and implementation of DVB-S signal in

passive radar imaging systems.

REFERENCES

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[6] P. Howland, "Editorial: Passive radar systems," IEE Proceedings-Radar, Sonar and Navigation, vol. 152, no. 3, pp. 105-106, 3 June 2005.

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[8] D. W. O'Hagan, H. Kuschel, et al., "Signal reconstruction as an effective means of detecting targets in a DAB-based PBR," presented at 2010 11th Internationa Radar Symposium, Vilnius, Lithuania, June 2010.

[9] M. K. Baczyk and M. Malanowski, "Decoding and reconstruction of reference DVB-T signal in passive radar systems," in Proc. 2010 11th International Radar Symposium, 16-18 June 2010, pp.1-4.

[10] X. Wan, B. Cen, et al., " Reference signal extraction methods for CMMB-based passive bistatic radar," Journal of Electronics & Information Technology, vol. 34, no. 2, pp. 338-343, Feb 2012.

[11] X. Wan, J. Wang, et al., "Reconstruction of reference signal for DTMB-based passive radar systems," in Proc. 2011 IEEE CIE International Conference on Radar, vol. 1, 24-27 Oct. 2011, pp. 165-168.

[12] China Satellite Communication. [Online]. Available: http://www.chinasatcom.com/cn/default.aspx.

[13] ETSI EN. 300 421 V1.1.2. Digital Video Broadcasting (DVB). Framing structure, channel coding and modulation for11/12 GHz satellite services, 1997.

Lu Hongchao graduated from the department of Electronic Engineering and Information Science(EEIS) of the University of Science and Technology of China (USTC). His main research interests are on directions of passive radar imaging and signal processing technology.

Liu Bing is an engineer of Military Representative Office of PLA in 209th Institute, graduated from the People's Liberation Army Ordnance Engineering College. His main research interest is on radar signal processing technology.

Guo Hongqi is an senior engineer of Military Representative Office of PLA in 209th Institute, graduated from Shaanxi Institute of Mechanical Engineering. He research on radar technology.

Huang Biao is an engineer of Military Representative Office of PLA in 209th Institute, graduated from the People's Liberation Army Ordnance Engineering College. His main research field is radar signal processing technology.



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