ADAPTIVE TARGET DETECTION IN PARTIALLY HOMOGENEOUS ENVIRONMENT FOR FDA-MIMO RADAR

被引：0
作者：
Li, Ping [1 ]
Huang, Bang [1 ]
Wang, Wen-Qin [1 ]
Basit, Abdul [2 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Chengdu 611731, Sichuan, Peoples R China
[2] Int Islamic Univ, Dept Comp & Elect Engn, FET, Islamabad, Pakistan
来源：
2024 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2024) | 2024年
关键词：
FDA-MIMO radar; adaptive detection; partially homogeneous environment; subspace model; generalized likelihood rate test (GLRT); constant false alarm rate (CFAR) property; GLRT; SUPPRESSION; CLUTTER; ARRAY; ANGLE;
D O I：
10.1109/IGARSS53475.2024.10641801
中图分类号：
P9 [自然地理学];
学科分类号：
0705 ; 070501 ;
摘要：
This paper investigates the adaptive target detection problem in FDA-MIMO radar embedded in Gaussian noise with an unknown covariance matrix, considering the scenario of mismatched steering vectors. Firstly, we assume that the covariance matrix of the test data and training data has the same structure with different magnitude levels. Next, the subspace model is adopted to enhance the robustness of the detector against mismatched signals. Furthermore, TS-GLRT detector is designed based on the generalized likelihood ratio test (GLRT), then we validated its constant false alarm rate (CFAR) property. Finally, simulation results demonstrate the effectiveness of the proposed approach.
引用
收藏
页码：9811 / 9818
页数：8
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