Matrix Information Geometry for Passive Sonar Signal Detection in a Non-Stationary Environment

被引：0

作者：

Hua, Xiaoqiang ^{[1
]}

Zhou, Zemin ^{[1
]}

Zeng, Yang ^{[1
]}

Lan, Qiang ^{[1
]}

Wang, Yongxian ^{[1
]}

Zhang, Lilun ^{[1
]}

Wang, Wenke ^{[1
]}

机构：

[1] Natl Univ Def Technol, Coll Meteorol & Oceanog, Changsha 410073, Hunan, Peoples R China

来源：

2019 IEEE 4TH INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING (ICSIP 2019) | 2019年

基金：

中国国家自然科学基金;

关键词：

power spectral density matrix; non-stationary; matrix information geometry; sonar signal detection; kullback-leibler divergence;

D O I：

10.1109/siprocess.2019.8868779

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

In this paper, a passive sonar signal detection based on the matrix information geometry theory in a non-stationary environment is proposed. Particularly, the power spectral density (PSD) matrix is the feature which is used for the signal detection. The noise power is estimated using the Kullback-Leibler divergence mean of the noise PSD matrices. The presence and absence of a target is determined by the distance between the PSI) matrix of the received signal and the mean matrix of noise. Simulation results show that the performance of our proposed method outperforms the energy detector in a non-stationary noise.

引用

页码：391 / 394

页数：4

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