Studies On Polarimetric SAR Imagery Man-made Target Detection

Polarimetric Synthetic Aperture Radar (PolSAR) is one of the most advancedsensors in the present remote sensing field. Using the polarimetric information for theman-made target detection in SAR image is a frontal subject in PolSAR imageinterpretation. It is of theoretical and practical importance in promoting the PolSARsystem for utilization. For the reasons above, grounded on the polarimetric informationdifferences between man made target and natural clutter, and aiming at the requirementof automatic target detection technique for polarimetric SAR image with compoundedclutter background and varies target types, this thesis deeply investigates some keytechniques such as the construct of the unsupervised polarimetric target detectionmetrics, the statistical modeling for the clutter of the metrics and the CFAR targetdetection etc. The main work includes the following aspects.Through theoretical analysis and experimental validation, we present the reason ofthe inefficient detection performance of2P-CFAR detector based on MPWF and SPANmetrics in the compounded background where the degree of the clutter varies vastly.Further, the detection technique of PMF metric including the statistical modeling, theparameter estimation and the CFAR detection are developed and improved. For thePMF metric, the constant, the Gamma distribution, the inverse Gamma distribution andthe inverse Gauss distribution is selected to characterize the distribution of the RCScomponent in the homogenous, heterogeneous, extremely heterogeneous and thecompounded areas, then the distributions of PMF metric are derived for thecorresponding area. In the parameter estimation, based on the SKS method, theparameter estimation expression of the derived distributions are converted into thesummation of the parameter estimation of PMF distribution in the homogenous area andthe parameter estimation of RCS distribution, thus simplifying the parameter estimationin the maximal degree. In the CFAR detection, based on the conclusion that thedistribution of PMF metric with the RCS modeled in inverse Gamma distribution hasmore extensive modeling capacity in various clutter area, the formula of the CFARdetection threshold of the correponding distribution is deduced. Then the CFARdetection with sliding window is designed, which improves the accuracy andpracticability of CFAR detection. The experimental results demonstrate the greatefficiency of the derived distributions and the corresponding parameter estimation ofPMF metric in the areas with different degree of homogeneity. Moreover, comparedwith the2P-CFAR detector based on MPWF and SPAN metrics, the proposed CFARdetector based on the PMF metric has better detection performance in complex clutterenvironment where the homogeneity of terrain varies sharply.(2) An unsupervised PolSAR image target detection method is proposed based on the scattering characteristic difference between man-made target and natural clutter.Through analyzing the polarimetric scattering mechanism of the common man-madetargets and natural clutters, the scattering characteristic and the major differencebetween man-made target and natural clutter is generalized. Then the effect of theorientation on the coherency matrices of the four component model is analyzed in detail.based on the analysis above, the orientation of the PolSAR data is compensated toremove the effect of the orientation to the scattering characteristics. Finally, using theorientation compensated data, the sum of double-bounce and helix scattering powerderived from the four-component model is extracted as the new metric. Afterward,according to the statistical characteristic of the new metric, a data fitting based targetdetection scheme is presented, which utilizes the G0distribution to fit the distribution ofPDEH metric. The experimental results demonstrate the great efficiency of orientationcompensation in increasing the scattering difference between the man made target andnatrual clutter and the derived metric has high SCR. Finally, the target detection schemeusing the G0distribution assures the accurate target detection in clutters with differentdegree of homogeneity.(3) A novel PolSAR unsupervised CFAR target detectionmethod is proposed basedon the characteristic polarization state of the canonical scatterers. Through analyzing thepolarization signature of the canonical scatterers in the co-polarized and cross-polarizedchannels, we select the characteristic polarization states which have the the minimalreceiving power for metallic plane and maximal receiving power for the dihedral in theco-polarized the cross-polarized channels, i. e., the left and the right circularpolarization state in the co-polarized channel and the45degree linear characteristicpolarization state in the cross-polarized channel as the canonical characteristicpolarization states for the target detection. Therefore, we compute the antenna receivingpower in the characteristic polarization states above as the new metrics and validate thelinear relationsip between the new metrics and PMF metric. Utilizing thefour-component decomposition model, we analyze the effect of new metrics on thetarget enhancement and clutter suppression, and the SCR relationship of the antennareceiving power with the polarimetric similarity theoretically. It can be seen the newmetrics include both the scattering similarity and the power information difference, thussuch metrics is provided with distinct target enhancement. In the target detectionsegment, according to the linear relationship between the new metrics and the PMFmetric, we realize the CFAR detection of new metrics using the target detection schemeof PMF metric. The experimental results demonstrate that the proposed metrics aresimple to obtain and have minimal computation load. Moreover, they are provided withthe advantadge of notable target enhancement and effcient detection performance.(4) A new polarimetric SAR CFAR target detector is proposed based on thereflection symmetry. Through analyzing the reflection symmetry difference between most of the man made targets and natural clutters, a new metric, which includes theinformation of the orientation distribution and the helicity of the scattering medium, isconstructed using the magnitude of the third off-diagonal term of the sample averagedcoherency matrix (the (2,3) term of the coherency matrix). In order to realize theparameter estimation and CFAR detection analytically, the statistical model of the newmetric is approximated and simplified in the homogenous area. Then grounded on thesimplified statistical model in the homogenous area, the statistical model of the newmetric is derived in the heterogeneous area by introducing the inverse Gammadistribution to characterize the distribution of RCS component. Based on the statisticalmodels, the parameter estimation and the automatic constant false alarm rate (CFAR)detection scheme are given in detail. The experimental results have demonstrated theproposed metric has the advantage of simple in computing, efficient and robust inclutter suppression and target enhancement. Moreover, the simplified distribution of theproposed metric has reasonable goodness of fit results in the homogenous clutter areasuch as sea, farmland etc, thus validating the rationality of the mathematicalapproximation. In the heterogeneous area, the derived distribution of the proposedmetric can also assure the precise modeling in vegetation area, urban and their mixedarea etc. Further more, the proposed approach can realize the precise CFAR targetdetection in the compounded background with the clutter varies vastly.