A new method of target detection for passive radar based on information accumulation

被引：0
|
作者：
Li B. [1 ]
Cen Z. [1 ]
Tang J. [1 ]
机构：
[1] Department of Electronic Engineering, Tsinghua University, Beijing
来源：
Journal of Radars | 2020年 / 9卷 / 06期
关键词：
Bayesian filtering; Information entropy; Passive radar; Target detection; Track-Before-Detect (TBD);
D O I：
10.12000/JR20023
中图分类号：
学科分类号：
摘要：
Owing to their strong anti-stealth performance, good concealment and strong survivability, passive radar systems have a wide range of applications in both military and civilian fields. We propose a method of target detection for passive radar systems which is based on the characteristics of these systems and the trackbefore- detect concept. This method accumulates information to effectively detect weak targets with low signalto- noise ratios and meet real-time requirements. First, we discretize the state space, then perform recursive Bayesian filtering to transfer and accumulate target-state information between multiple frames. Lastly, the information entropy is used to determine whether the target exists, thereby avoiding reliance on a prior assumption about the transition probability model between the existence and the absence of the target. This method is simple to implement and has low computational complexity and high parallelism. The experimental results indicate that the proposed method has a short running time and strong real-time performance, as well as good detection performance and robustness. © 2020 Institute of Electronics Chinese Academy of Sciences. All rights reserved.
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页码：959 / 966
页数：7
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