Persymmetric adaptive target detection with distributed MIMO radar

Jun Liu, Hongbin Li, Braham Himed

Research output: Contribution to journalArticlepeer-review

66 Scopus citations

Abstract

Based on persymmetric structures in received signals, we consider the adaptive detection problem in colored Gaussian noise with unknown persymmetric covariance matrix in a multiple-input, multiple-output (MIMO) radar with spatially dispersed antennas. To this end, a set of secondary data for each transmit-receive pair is assumed to be available. A MIMO version of the persymmetric generalized likelihood ratio test (MIMO-PGLRT) detector is proposed. A closed-form expression for the probability of false alarm of this detector is derived. In addition, a MIMO version of the persymmetric sample matrix inversion (MIMO-PSMI) detector is also developed. Compared to the MIMO-PGLRT detector, MIMO-PSMI has a simpler form and is computationally more efficient. Numerical examples are provided to demonstrate that the proposed two detection algorithms can significantly alleviate the requirement of the amount of secondary data and allow for a noticeable improvement in detection performance.

Original languageEnglish
Article number7073498
Pages (from-to)372-382
Number of pages11
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume51
Issue number1
DOIs
StatePublished - 1 Jan 2015

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