Polarimetric Detection and Range Estimation of a Point-Like Target

In this paper, we deal with the problem of polarimetric diversity detection for point-like targets in the presence of Gaussian clutter with unknown covariance matrix. To this end, we jointly exploit the polarization diversity and the spillover of target energy to consecutive range samples to improve the performances of detection and range localization. For estimation purposes, we assume that a set of secondary data (free of signal components) is available with the same covariance matrix as the clutter in the cells under test. Because the uniformly most powerful test does not exist for this problem, we derive two adaptive detectors: the generalized likelihood ratio test and the Wald test. Interestingly, these new receivers ensure the constant false alarm rate property with respect to covariance matrix of the clutter. The performance assessments conducted on both simulated data and real recorded dataset reveal that the proposed detectors outperform, in both detection and localization, the traditional state-of-the-art counterparts that ignore either the polarimetry or the spillover.