An Augmented Generalized Likelihood Ratio Test Detector for Signal Detection in Clutter and Noise

被引：2

作者：

Tang, Hui ^{[1
]}

Chai, Li ^{[1
]}

Wan, Xianrong ^{[2
]}

机构：

[1] Wuhan Univ Sci & Technol, Engn Res Ctr Met Automat & Measurement Technol, Wuhan 430081, Peoples R China

[2] Wuhan Univ, Sch Elect Informat, Wuhan 430072, Peoples R China

来源：

IEEE ACCESS | 2019年 / 7卷

基金：

中国国家自然科学基金;

关键词：

Detection; generalized likelihood ratio test (GLRT); matched subspace detector; generalized Marcum Q-function; DISTURBANCE REMOVAL; ADAPTIVE DETECTION; TARGET DETECTION; RADAR; ALGORITHM;

D O I：

10.1109/ACCESS.2019.2952404

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

To deal with the problem of signal detection in correlated subspace, this paper presents an augmented generalized likelihood ratio test (AGLRT) detector. Compared with traditional GLRT detector, this AGLRT detector has the advantage of incorporating the intersection component between signal and clutter subspace. Signal-contribution-ratio (SCR) and clutter-contribution-ratio (CCR) are defined to characterize the contribution of signal and clutter in the common subspace, respectively. The closed forms of both probability of detection and false alarm for the AGLRT detector are presented. It is shown that the detection performance of the AGLRT detector is better than the GLRT detector by choosing appropriate weight and threshold parameters. Then, analytical formulas of the suboptimal weight and threshold to maximize the detection performance are obtained. Finally, the effectiveness of the proposed detector is demonstrated by various examples.

引用

页码：163478 / 163486

页数：9

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