Multiple Subspace-Based Target Detection in Deterministic Interference

被引：0
|
作者：
Sun, Mengru [1 ]
Liu, Weijian [2 ]
Liu, Jun [3 ]
Hao, Chengpeng [4 ]
Li, Kefei [1 ]
机构：
[1] Chinese Acad Sci, Inst Acoust, Qingdao Branch, Qingdao 266114, Peoples R China
[2] Wuhan Elect Informat Inst, Wuhan 430019, Peoples R China
[3] Univ Sci & Technol China, Dept Elect Engn & Informat Sci, Hefei 230027, Peoples R China
[4] Chinese Acad Sci, Inst Acoust, Beijing 100190, Peoples R China
来源：
IEEE SIGNAL PROCESSING LETTERS | 2024年 / 31卷
基金：
中国国家自然科学基金;
关键词：
Adaptive detection; deterministic interference; Kullback-Leibler information criterion; model order selection; multiple hypothesis test; ADAPTIVE RADAR DETECTION; PART I; UNIFYING FRAMEWORK; HOMOGENEOUS NOISE; GLRT; RAO;
D O I：
10.1109/LSP.2024.3491012
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this letter, the problem of detecting a multiple subspace-based target in the presence of deterministic interference is considered. To solve the problem, we utilize the Kullback-Leibler information criterion and model order selection rules to design detection schemes. The alternative hypothesis related to the most likely signal subspace is selected from multiple alternative hypotheses, and is tested versus the null hypothesis for target detection. Numerical examples verify the effectiveness of the proposed detection schemes, which can achieve the target detection and subspace-based target classification simultaneously.
引用
收藏
页码：3134 / 3138
页数：5
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