Polarimetric ABORT-like adaptive detector in the presence of target steering vector mismatch

In this paper, a robust polarimetric detector is presented to deal with the problem of target steering vector mismatch. Within the framework of the adaptive beamformer orthogonal rejection test (ABORT), the decision statistic of the proposed polarimetric detector involves the estimates of the polarimetric clutter-plus-noise covariance matrix of the secondary data, the target vector after primary data whitening and dual polarimetric channel unitary transformation, and the sidelobe interference vector which is polarimetricly and spatially orthogonal to the target vector after primary data whitening. With the polarimetric and spatial joint subspace constraint, the interference vector is estimated from the Bayesian estimate of the clutter-plus-noise covariance matrix. To obtain a more reliable estimate of the target vector after primary data whitening and unitary transformation, two separate conic uncertainty set constraints are incorporated into a least square fitting scheme. A modified version of the detector is also given for the case of ground clutter. Simulations show that, in the presence of several types of target steering vector mismatch, the proposed detector achieves a considerable performance improvement over the traditional polarimetric adaptive detectors in terms of the probability of detection.