Adv. Radio Sci., 11, 291–295, 2013www.adv-radio-sci.net/11/291/2013/doi:10.5194/ars-11-291-2013© Author(s) 2013. CC Attribution 3.0 License.

Advances inRadio Science

Quantitative data analysis of ESAR data

N. Phruksahiran and M. Chandra

Professorship of Microwave Engineering and Electromagnetic Theory, Chemnitz University of Technology, Germany

Correspondence to:N. Phruksahiran (narathep.phruksahiran@s2009.tu-chemnitz.de)

Abstract. A synthetic aperture radar (SAR) data processinguses the backscattered electromagnetic wave to map radarreflectivity of the ground surface. The polarization prop-erty in radar remote sensing was used successfully in manyapplications, especially in target decomposition. This pa-per presents a case study to the experiments which are per-formed on ESAR L-Band full polarized data sets from Ger-man Aerospace Center (DLR) to demonstrate the potentialof coherent target decomposition and the possibility of usingthe weather radar measurement parameter, such as the differ-ential reflectivity and the linear depolarization ratio to obtainthe quantitative information of the ground surface. The rawdata of ESAR has been processed by the SAR simulator de-veloped using MATLAB program code with Range-Doppleralgorithm.

1 Introduction

Nowadays, SAR Technology has been continuously devel-oped by many researchers. Therefore, many benefits of po-larimetric SAR (PolSAR) by using the physically propertiesof scattering mechanisms in the polarization signature wasfound. This leads to many theories and applications in thefield of target decomposition. The polarimetric decomposi-tion theorems can be classified into coherent and incoherenttarget decompositions which have each different advantage.The coherency decomposition deal with the scattering ma-trix, the incoherent decomposition is based on the coherencyor covariance matrices. In addition to the full polarimetricSAR systems that transmit two orthogonal polarizations andrecord both received polarization, i.e., (hh, hv, vh, vv), whereh and v denote the horizontal and vertical polarizations, re-spectively, there is the so-called dual-pol SAR modes, thatconsider only two linear polarizations, i.e., (hh,hv), (vh,vv)and (hh,vv). Another parameter of interest are the differen-tial reflectivity(Zdr) and the linear depolarization ratio(Ldr),

that can be used to process the weather radar data to obtainthe qualitative measurements.

In this paper, SAR simulator was developed by usingMATLAB program in order to process the experimental datafrom DLR with Range-Doppler processing algorithm. Theprocessed full-polarized data was used to investigate thesome potential of the coherent decompositions in SAR po-larimetry.

This paper is organized as follows. In Sect. 2 we intro-duce the basics of the target decomposition, and in Sect. 3we explain the experimental data and the data processing. InSect. 4, the simulation results are presented. Finally, Sect. 5provides the conclusions.

2 Basics

In general, the radar image of SAR system presents the mag-nitude of each pixel which can be scaled to show the depthof the image, so that we can interpret it like the optical im-age. The visual analysis needs the correct perception of theobserver to identify the targets on the ground. The target de-composition theorems are developed based on the wave po-larization basis to aim at providing such an interpretation.

The main categories of decompositions and parameterconsidered in this paper are the following: Pauli decompo-sition, differential reflectivity and linear depolarization ratio.

2.1 Pauli decomposition

Pauli decomposition is the most common known decompo-sition and expresses the scattering matrix[S] as the complexsum of the Pauli matrices which can be written as shown byLee(2009):

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292 N. Phruksahiran and M. Chandra: Quantitative data analysis of ESAR data

[S] =

[Shh ShvSvh Svv

](1)

=a

√2

[1 00 1

]+

b√

2

[1 00 −1

]+

c√

2

[0 11 0

]+

d√

2

[0 −j

j 0

](2)

The parametera,b,c andd are complex quantities repre-senting, respectively, single or odd-bounce scattering, doubleor even-bounce scattering, 45◦ rotated double-bounce scat-tering, and the anti-symmetric components of the scatteringmatrix, and are given by:

a =Shh+ Svv

√2

(3)

b =Shh− Svv

√2

(4)

c =Shv + Svh

√2

(5)

d = jShv − Svh

√2

. (6)

In the case of the monostatic radar operation, it is assumedthatShv = Svh, and the Span value is given by:

Span= |Shh|2+ 2|Shv|

2+ |Svv|

2= |a|

2+ |b|

2+ |c|2 . (7)

The color-coded representation with the basic colors (red,blue, green) can be used to recreate the image correspond-ing to the color-coded of each complex quantity.

2.2 Differential reflectivity and linear depolarizationratio

The differential reflectivity(Zdr) and the linear depolariza-tion ratio (Ldr) are commonly used in weather radar mea-surements. At the weather radar, the target volume is takenfor analysis. The SAR system receives the reflected signalsof ground targets and processes the data to the final imagethat represents the reflection properties of the ground.

The differential reflectivityZdr can be calculated in dB asthe ratio of the reflectivity in horizontal polarizationShh andthe reflectivity in vertical polarizationSvv by the followingequation as shown byYanovsky(2000):

Zdr = 10· log10Shh

Svv. (8)

The important information from theZdr value depends onthe target structure. IfZdr is closely zero, the structure issphere. The structure has the more length in horizontal axiswhen theZdr value is more than zero. Adversely, theZdrvalue is less than zero then, the structure has the more lengthin vertical axis.

The linear depolarization ratioLdr is one of the interestingratios from measurement and is the fraction of refractivity

Fig. 1.Google Earth image of the test area.

between the co- and cross-polar radar signal channels by thefollowing equation:

Ldr = 10· log10Svh

Shh. (9)

3 Experimental data and data processing

The experimental L-Band full polarized of Opairfield TestSite Area of Germany data set, which was used in this paper,is from the airborne ESAR flown by the German AerospaceCenter (DLR), obtained on 20 February 2003. The terrain, asshown in Fig.1, is a mixture of the flat surfaces, trees andbuildings.

There are numerous SAR simulators for development ofa radar system and radar processing. In this paper the rangeDoppler algorithm have been chosen to process the SAR rawdata from ESAR.

The overview of the ESAR data signal processing withrange Doppler algorithm and the target decomposition isshown in Fig.2. The SAR simulator program was developedto read the binary raw data and to convert it to the two dimen-sion SAR matrices data in range and azimuth direction for thefollowing data processing as shown byCumming(2005).

In each step of the SAR data processing, the requiredsystem parameters, the frequency, the bandwidth, the pulselength and the geometry, have been added into the simula-tion program. The signal processing in this paper with rangeDoppler algorithm in frequency domain takes place in or-der of range compression, range migration correction andazimuth compression. The range compression is performedwhen the data are in the azimuth time domain with a fastconvolution by using the matched filter function in the rangedirection. The range migration correction is performed in therange Doppler domain to straighten out the target trajectoriesat the same range into on single trajectory that run parallel

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N. Phruksahiran and M. Chandra: Quantitative data analysis of ESAR data 293

Fig. 2. Functional block diagram of ESAR signal processing withrange Doppler algorithm and target decomposition.

Fig. 3. Image data of hh-polarization channel from ESAR (DLR).

to the azimuth frequency axis. The azimuth compression isperformed by using the matched filter function at each rangegate. Then the processed data of the respective polarizationchannels are used for the purpose of target decomposition.

4 Results

This section presents the simulation results for the purposeof the alternative or supplement information of polarimetricSAR data to the existing target decomposition methods.

4.1 Image data

After digital signal processing, the four polarized data setshave been created in hh, hv, vh and hv polarization. The Im-age data can be shown with gray scale by using the differenceof signal intensity from the target or the surface of interest.The signal intensity depends on the scattering properties ofeach target structure according to the polarization state of theSAR operation. In this paper, we used the Range-Doppler al-gorithm to process each SAR data channel, i.e., hh, hv, vhand vv, with the same system parameter and data processingin frequency domain.

Fig. 4. Pauli decomposition, the image is colored by blue for|a|2;red for|b|2; green for|c|2.

Figure3 presents the image data of ESAR data set in hhpolarization after the signal processing with Range-Doppleralgorithm with sub-aperture length in azimuth direction andwithout the multi-look processing to reduce the speckle noisewhich arises in SAR because the relative phase of individualscatters. So that we can get and use the original image dataset to test the target decomposition method and quantitativeparameter of radar image as following.

4.2 Pauli decomposition

In general, the Pauli decomposition provides a tool for im-age classification that has been well known for decades inradar remote sensing communities. The three component ofthe Pauli composition are represented with color-coded blue,|a|

2; red,|b|2 and green,|c|2, respectively. Figure4 presents

the corresponding color-coded Pauli reconstructed image.If we compare Fig.1 with Fig. 4, we can realize the Pauli

signatures of each part on the test area. The area on the rightabove is the residential area with many houses, which havethe structure of dihedral, the red color dominates. The run-way and street areas are presented by dark tone. It is clearto see that the forest area is in green. The areas in whichthe scattering mechanisms are simultaneously presented areshown with white. The different colors show that each polar-ization provides other information.

4.3 Differential reflectivity and linear depolarizationratio

In order to provide alternative verification of the differentialreflectivity and linear depolarization ratio in SAR target de-composition method, the simulated images are provided inFig. 5 and Fig.6 for differential reflectivity and linear depo-larization ratio, respectively.

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294 N. Phruksahiran and M. Chandra: Quantitative data analysis of ESAR data

Fig. 5.Simulation results ofZdr of test site area in dB.

4.3.1 Zdr values

Figure5 presents the simulation results of differential reflec-tivity by using the reflectivity difference between hh- and vvpolarization SAR operation. The values are shown in dB withthe value range[−10,10].

By using the color-coded according to theZdr values, onecan see that there are different shades of each area on theimage. When considered as a whole, it can be seen that thesmooth area has theZdr values less than zero, the blue colordominates. The another area which consists of a building orarea of forest has theZdr values more than zero, the red colordominates. In the area of forest and building, there is notmuch of difference from each other. By using the differentialreflectivity, we can see and image the contour of the groundstructure and it can be separated the flat area from the areawith forest and building.

4.3.2 Ldr values

Figure6 presents the simulation results of linear depolariza-tion ratio by using the reflectivity difference between vh- andhh polarization SAR operation. The values are shown in dBwith the value range[−10,10].

The values of linear depolarization ratio as shown in Fig.6have the uneven distribution. But one can indicate that thevalues ofLdr are less than zero for the smooth area and thevalues ofLdr are more than zero for the area with buildings.

4.3.3 AppliedZdr values

In Fig. 5, we have defined a continuous change of color-coded of the differential reflectivity values to compare thevalues obtained from the experiments, so that we can see theapproximately difference between each type of surface.

Fig. 6.Simulation results ofLdr of test site area in dB.

Fig. 7.AppliedZdr values with−1 and 1.

Figure7 presents the simulation results of differential re-flectivity by using the reflectivity difference between hh- andvv polarization SAR operation. The values are shown with−1 and 1 for theZdr values which are less than zero and theZdr values which are equal or more than zero, respectively.

The applied adjustment of the display color-coded makesit possible to see the lines and the contour of the surface char-acter. Although it cannot be stated clearly that the surfacelooks like or consists of any object type. The target decom-position by using the appliedZdr values can provide infor-mation correctly that the ground surface is flat or that thebuildings or the forests are in the area. In this paper, it canbe determined that if the surface is smooth, the value of the

Adv. Radio Sci., 11, 291–295, 2013 www.adv-radio-sci.net/11/291/2013/

N. Phruksahiran and M. Chandra: Quantitative data analysis of ESAR data 295

Fig. 8.AppliedLdr values with−1 and 1.

variableZdr are equals to−1 and if the surface is not smooth,the value of the variableZdr are equals to 1.

4.3.4 AppliedLdr values

The same approach to the display the appliedZdr values inFig. 7 has been used to present the simulation results of thelinear depolarization ratio from the Fig.6, so that the valuesin the Fig.8 are shown with−1 and 1 for theLdr valueswhich are less than zero and theLdr values which are equalor more than zero, respectively.

The benefit of this approach is the values ofLdr in thearea with large buildings. By comparing the location of thebuilding in Fig.1 one can see the border of the building inFig. 8 at the same location as well.

4.4 Comparison of appliedZdr values and appliedLdrvalues

By comparing the values of the applied differential reflec-tivity in Fig. 7 and the applied linear depolarization ratio inFig. 8 at each area, it can be divided in four cases as follow-ing:

1. +Zdr and+Ldr: the areas that may have a positiveZdrvalues and positiveLdr values are larger building.

2. +Zdr and −Ldr: in the vicinity of the houses or vil-lages with a characteristic dihedral structure, theZdrmay have a positive values but theLdr may have neg-ative values.

3. −Zdr and+Ldr: in this case, it is not posible to deter-mine exactly what are the surface characteristics and thekind of target.

4. −Zdr and−Ldr: the simulation results also indicate thatthe flat area and fields may have the negative values ofZdr andLdr.

5 Conclusions

In the first part of this paper, we have provided a short reviewof Pauli decomposition, differential reflectivity and linear de-polarization ratio. The SAR simulator was developed to pro-cess the polarimetric raw data set of ESAR from DLR withrange Doppler algorithm. The findings indicate that some pa-rameter which was used to evaluate weather data set such asdifferential reflectivity and linear depolarization ration canbe used for the decomposition purpose in SAR radar remotesensing and they are considered as a useful addition to thedecomposition theorems. Since the simulation results are ob-tained with only one polarimetric test data set, the interpre-tation and the conclusion have particular limitation. Furtherwork will also include the development of improved simula-tion method for a better interpretation of the various targetdecompositions, in particular the alternative measurementparameter, e.g., the differential reflectivity and the linear de-polarization, as an additional feature of the target decompo-sition method in SAR image data.

Acknowledgements.The authors would like to thank Al-berto Moraira of DLR, Germany, for providing the full polarimetricESAR data set which was used in EU project AMPER.

References

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Lee, J. S. and Pottier, E.: Polarimetric Radar Imaging from Basicsto Applications, CRC Press, Boca Raton, 2009.

Yanovsky, F. J., Russchenberg, H. W. J., Ligthart, L. P., andFomichev, V. S.: Microwave Doppler-polarimetric technique forstudy of turbulence in precipitation, in: Proceedings of IGARSS2000, Honolulu Hawaii, USA, 24–28 July 2000, 2296–2298,2000.

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