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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
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https://hal-centralesupelec.archives-ouvertes.fr/hal-02492079
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Submitted on : Wednesday, February 26, 2020 - 4:15:47 PM
Last modification on : Tuesday, September 27, 2022 - 3:38:41 AM

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  • HAL Id : hal-02492079, version 1

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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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