Adaptive persymmetric detector of generalised likelihood ratio test in homogeneous environment. Issue 2 (1st April 2016)

• Record Type: Journal Article
• Authors: Jian, Tao; He, You; Liao, Guisheng; Guan, Jian; Dong, Yunlong
• Is Part Of: IET signal processing. Volume 10:Issue 2(2016)
• Page Start: 91
• Page End: 99
• Publication Date: 2016-04-01
• Subjects: radar detection -- Monte Carlo methods -- covariance matrices; adaptive persymmetric detector -- generalised likelihood ratio test -- homogeneous environment -- adaptive detection -- radar target -- homogeneous Gaussian disturbance -- persymmetric covariance matrix -- unstructured GLRT -- secondary data -- false alarm -- false detection -- Monte Carlo simulations -- structured persymmetric adaptive matched filter -- training‐deficient scenarios; Signal processing -- Periodicals; 621.3822
• DOI: 10.1049/iet-spr.2015.0200
• Languages: English
• ISSNs: 1751-9675

Abstract

Abstract : Adaptive detection of radar target embedded in homogeneous Gaussian disturbance is addressed, by exploiting the persymmetric covariance matrix. On the basis of the decision schemes of generalised likelihood ratio test (GLRT), an adaptive persymmetric detector with constant false alarm rate property is designed, which can mitigate the demanding requirement of secondary data. Furthermore, the expressions for the probabilities of the false alarm and detection are derived, and the validity of them is confirmed by Monte Carlo simulations. The assessment results show that the proposed detector outperforms the conventional unstructured GLRT, the structured persymmetric adaptive matched filter and the persymmetric Rao detector, especially in the training‐deficient scenarios.