ALow Threshold CFAR Based TBD Algorithm
申俊星 SHEN Jun-xing
(商丘职业技术学院,商丘476000 )
( Shangqiu Polytechnic,Shangqiu 476000,China)
摘要;相比于先检测后跟踪的方法,检测前跟踪在低信噪比环境中有更加优秀的效果。本文提出一种适用于应用在雷达系统中的检测前跟踪方法,利用低门限CFAR与DP-TBD级联的方法,再经过检测门限判决,解决了TBD检测在雷达系统中的时间牺牲问题，并优化了DP-TBD的算法,降低复杂度,给出了低门限CFAR的门限取值方法,仿真结果表明,本文提出的算法在4帧积累时比传统的CFAR检测信噪比改善了约4.5dB。
Abstract:Compared to the method of delecting before tracking, tracking before detection has better performance in low signal-to=noiseratio environments. This article proposes a pre detection tracking method suitable for application in radar systems， which utilizes a lowthreshold CFAR and DP-TBD cascade method, and then solves the time sacrifice problem of TBD detection in radar systems throughdetection threshold judgment. DP-TBD algorithm is optimized to reduce complexity, and a threshold value method for low threshold CFARis provided.Sinmulation results show that, the algorithm proposed in this article improves the signal-to-noise ratio by approximately 4.5dBcompared to traditional CFAR detection when accumulating 4 frames.
关键词:动态规划;检测前跟踪;低门限CFAR;关联积累
Key words: dynamic programming; pre-detection tracking; low threshold CFAR; related accumulation
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