On the performance of a persymmetric adaptive matched filter

Jun Liu, Guolong Cui, Hongbin Li, Braham Himed

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

Abstract

We examine the adaptive detection problem in the presence of colored noise with an unknown covariance matrix, by exploiting a persymmetric structure in the received signal. The persymmetric adaptive matched filter (PS-AMF) is used to address this problem, which can significantly alleviate the requirement of secondary data. In G. Pailloux et al. "Persymmetric adaptive radar detectors," (2011) the probability of false alarm of the PS-AMF has been obtained in terms of the Gaussian hypergeometric function. In this paper, finite-sum expressions for the probability of false alarm of the PS-AMF are derived, which are more convenient to use in calculating the detection threshold. Moreover, the detection probabilities of the PS-AMF for both nonfluctuating and fluctuating target models are derived. In the fluctuating model, the amplitude of the target echoes is described by a generalized Chi distribution that involves the Rayleigh distribution as a special case. These theoretical results are all confirmed using Monte Carlo (MC) simulations.

Original languageEnglish
Article number140633
Pages (from-to)2605-2614
Number of pages10
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume51
Issue number4
DOIs
StatePublished - Oct 2015

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