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2012-06-21

Adaptive Detection of Multiple Point-Like Targets Under Conic Constraints

By Chengpeng Hao, Francesco Bandiera, Jun Yang, Danilo Orlando, Shefeng Yan, and Chaohuan Hou
Progress In Electromagnetics Research, Vol. 129, 231-250, 2012
doi:10.2528/PIER12040208

Abstract

This paper addresses the problem of detecting multiple point-like targets in the presence of steering vector mismatches and Gaussian disturbance with unknown covariance matrix. To this end, we first model the actual useful signal as a vector belonging to a proper cone whose axis coincides with the whitened direction of the nominal array response. Then we develop two robust adaptive detectors resorting to the two-step GLRT-based design procedure without assignment of a distinct set of secondary data. The performance assessment has been conducted by Monte Carlo simulation, also in comparison to previously proposed detectors, and confirms the effectiveness of the newly proposed ones. In the last part of the work, in order to restore the detection performance of the newly proposed detectors in the presence of a large number of range cells contaminated by useful signals, we consider two adaptive detectors which resort to the structure information of the disturbance covariance matrix, and show that the a-priori information on the covariance structure can lead to a noticeable performance improvement.

Citation


Chengpeng Hao, Francesco Bandiera, Jun Yang, Danilo Orlando, Shefeng Yan, and Chaohuan Hou, "Adaptive Detection of Multiple Point-Like Targets Under Conic Constraints," Progress In Electromagnetics Research, Vol. 129, 231-250, 2012.
doi:10.2528/PIER12040208
http://jpier.org/PIER/pier.php?paper=12040208

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