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Adaptive Detection Algorithms for Slow Moving Targets in Non-Gaussian Clutter

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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
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Dates and versions

hal-02492079 , version 1 (26-02-2020)

Identifiers

  • HAL Id : hal-02492079 , version 1

Cite

Narayan Bernardin, Claude Adnet, Jean-Philippe Ovarlez, Frédéric Barbaresco. Adaptive Detection Algorithms for Slow Moving Targets in Non-Gaussian Clutter. IEEE Radar Conference, Sep 2019, Toulon, France. ⟨hal-02492079⟩
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