Abstract

In this paper we present a new method for automatic target/object classification by using the optimum polarimetric radar signatures of the targets/objects of interest. The state-of-the-art in radar target recognition is based either on the use of single polarimetric pairs or on the four preset pairs of orthogonal polarimetric signatures. Due to these limitations polarimetric radar processing has been fruitful only in the area of target detection. It has not shown promise for improving target classification/recognition performance. The use of optimum polarimetric features for enhancing target recognition using synthetic aperture radar is explored in this paper. The polarization scattering matrix is used for the derivation of target signatures at arbitrary transmit and receive polarizations (arbitrary polarization inclination angles and ellipticity angles). Then an optimization criterion that minimizes the within class distance and maximizes the between class metrics is used for the derivation of optimum sets of polarimetric signatures. Then from sets of real fully polarimetric SAR imagery arbitrary polarization attributes are extracted. The performance of the automatic target detection and recognition algorithms using optimum sets of polarimetric signatures are derived and compared with those associated with the non-optimum signatures. The results show that noticeable improvements can be achieved by using the optimum over non- optimum signatures.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

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