Adaptive Detection Algorithms for Slow Moving Targets in Non-Gaussian Clutter
Abstract
The purpose of this paper is to present a study of non-Gaussian detectors for the detection of small, slow moving targets in clutter. These detectors belong to the family of Adaptive Normalized Matched Filter. The noise-clutter covariance matrix will be computed by the classic fixed point estimator [1, 2, 3] or with an iterative estimator based on the multi-segment Burg algorithm [4]. We will also propose to add a data selection algorithm based on order statistics in order to improve the estimation of this covariance matrix when targets are in the clutter alone reference cells