GLRT-Based Adaptive Target Detection in FDA-MIMO Radar

被引:172
作者
Lan, Lan [1 ]
Marino, Angela [2 ]
Aubry, Augusto [2 ]
De Maio, Antonio [2 ]
Liao, Guisheng [1 ]
Xu, Jingwei [1 ]
Zhang, Yuhong [3 ]
机构
[1] Xidian Univ, Natl Key Lab Radar Signal Proc, Xian 710071, Peoples R China
[2] Univ Naples Federico II, Dept Elect Engn & Informat Technol, I-80125 Naples, Italy
[3] Xidian Univ, Sch Elect Engn, Xian 710071, Peoples R China
关键词
Interference; Maximum likelihood estimation; Receivers; Radar detection; Computer architecture; Object detection; Frequency diverse array multiple-input multiple-output (FDA-MIMO) radar; generalized likelihood ratio test (GLRT); maximum likelihood (ML); Newton-based refinement; semidefinite programming (SDP); trigonometric polynomial functions;
D O I
10.1109/TAES.2020.3028485
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
This article deals with the problem of adaptive target detection in the presence of homogeneous Gaussian interference with frequency diverse array multiple-input multiple-output radar. Adaptive detectors are devised according to the generalized likelihood ratio test criterion, where the position of the target within each range cell is assumed unknown. To obtain the maximum likelihood estimate of the target incremental range under the $H_1$ hypothesis, three different optimization strategies are pursued. They are, respectively, based on semidefinite programming, discrete grid search, and Newton method. At the analysis stage, a detection performance comparison is carried on among the new proposed adaptive detectors, benchmark, and mismatched receivers. Numerical results corroborate the effectiveness of the developed receivers.
引用
收藏
页码:597 / 613
页数:17
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