DocumentCode :
3389459
Title :
A persymmetric detector with enhanced selectivity properties
Author :
Chengpeng Hao ; Chaohuan Hou ; Xiaochuan Ma ; Shefeng Yan ; Orlando, Danilo
Author_Institution :
State Key Lab. of Acoust., Inst. of Acoust., Beijing, China
fYear :
2013
fDate :
1-3 July 2013
Firstpage :
1
Lastpage :
5
Abstract :
In this paper, we deal with the problem of adaptive detection of point-like targets in Gaussian disturbance with unknown but persymmetric structured covariance matrix induced by a symmetric antenna geometry. In particular, at the design stage we modify the noise-only hypothesis assuming the presence of a fictitious signal orthogonal to the nominal one. The performance assessment, conducted by Monte Carlo simulation, has shown that the proposed receiver can significantly outperform its unstructured counterpart and guarantee enhanced rejection performance of unwanted signals.
Keywords :
Monte Carlo methods; covariance matrices; object detection; Gaussian disturbance; Monte Carlo simulation; antenna geometry; covariance matrix; noise-only hypothesis; persymmetric detector; point-like targets adaptive detection; Covariance matrices; Detectors; Monte Carlo methods; Receivers; Signal to noise ratio; Vectors; Adaptive detection; generalized likelihood ratio test (GLRT); persymmetry;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Signal Processing (DSP), 2013 18th International Conference on
Conference_Location :
Fira
ISSN :
1546-1874
Type :
conf
DOI :
10.1109/ICDSP.2013.6622785
Filename :
6622785
Link To Document :
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