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On Persymmetric Covariance Matrices in Adaptive Detection

Abstract : In the general area of radar detection, estimation of the clutter covariance matrix is an important point. This matrix commonly exhibits a persymmetric structure: this is the case for instance for active systems using a symmetrically spaced linear array or pulse train. In this context, this paper provides a new Gaussian adaptive detector called the persymmetric adaptive matched filter (P-AMF). Its theoretical distribution is derived allowing adjustment of the detection threshold for a given probability of false alarm (PFA). Simulations results highlight the improvement in term of probability of detection (PD) of the P-AMF in comparison with the classical adaptive matched filter (AMF).
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https://hal-supelec.archives-ouvertes.fr/hal-00353608
Contributor : Anne-Hélène Picot <>
Submitted on : Thursday, January 15, 2009 - 6:09:49 PM
Last modification on : Wednesday, October 14, 2020 - 3:57:00 AM

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G. Pailloux, Philippe Forster, Jean-Philippe Ovarlez, Frédéric Pascal. On Persymmetric Covariance Matrices in Adaptive Detection. 2008 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008), Mar 2008, Las Vegas, United States. ⟨10.1109/ICASSP.2008.4518107⟩. ⟨hal-00353608⟩

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