基于统计量ODV的自适应TM-CFAR检测

doi:10.13190/jbupt.201302.64.duhm

北京邮电大学学报 ›› 2013, Vol. 36 ›› Issue (2): 64-69.doi: 10.13190/jbupt.201302.64.duhm

基于统计量ODV的自适应TM-CFAR检测

杜海明^1,2, 马洪¹, 杜保强³

1. 华中科技大学电子信息工程系, 武汉 430074; 2. 郑州轻工业学院电气信息工程学院, 郑州 450002; 3. 西安电子科技大学雷达信号处理国家重点实验室, 西安 710071

收稿日期:2012-05-19 修回日期:2012-11-23 出版日期:2013-04-30 发布日期:2013-03-25
通讯作者: 杜海明 E-mail:duhaiming-007@163.com.
作者简介:杜海明（1977-），男，博士生，Email：duhaiming-007@163.com；马洪（1966-），男，教授，博士生导师
基金资助:
国家"十一五"科技支撑计划子课题（2008BAC3B00）；国家自然科学基金项目（10978107,60772135）

Adaptive TM-CFAR Detection Based on the Statistics ODV

DU Hai-ming^1,2, MA Hong¹, DU Bao-qiang³

1. Department of Electronic and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;<br>2. College of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China;<br>3. National Laboratory of Radar Signal Processing, Xidian University, Xian 710071, China

Received:2012-05-19 Revised:2012-11-23 Online:2013-04-30 Published:2013-03-25
Contact: du haiming E-mail:duhaiming-007@163.com.

摘要/Abstract

摘要：

基于有序数据变率(ODV)和削减平均恒虚警(TM-CFAR)检测,提出了自适应TM-CFAR检测,它能判决自动选择参数并估计背景噪声,仿真结果表明,在均匀背景和多目标背景下,其具有较好的检测性能,能提高抗干扰目标最大容限;在强杂波边缘时,其虚警概率控制能力优于有序统计CFAR检测和单元平均CFAR检测. 采用两级结构和分块并行处理思想实现时,该算法所需硬件资源和运算复杂度都低于自动删除平均ODV检测,而且具有实时处理性高和时序控制方便的优点.

关键词: 有序数据变率, 削减平均恒虚警检测, 自适应检测, 均匀背景

Abstract:

Adaptive trimmed mean constant false alarm rate (ATM-CFAR) detection based on TM-CFAR detection and statistics ordered data variability (ODV) is presented. These parameters and background estimations can be selected automatically. Simulation shows that the algorithm has good detection performance under homogeneous environment and multi-target environment, and also increases its tolerance of interfering targets. Moreover, under high clutter noise ratio at clutter edge regions, the control ability on false alarm rate is much better than that of cell average CFAR detection and ordered statistics CFAR detection. Using two-level architecture and sub-block parallel processing methods, its hardware implementation and computational complexity are less than the automatic censored cell-averaging based on the statistics ODV by on-chip implementation. Furthermore, it also has the advantages of high real-time processing and is very convenient for sequential control in practice.

Key words: ordered data variability, trimmed mean constant false alarm rate detection, adaptive detection, homogenous environment

中图分类号:

TN911.7

杜海明, 马洪, 杜保强. 基于统计量ODV的自适应TM-CFAR检测[J]. 北京邮电大学学报, 2013, 36(2): 64-69.

DU Hai-ming, MA Hong, DU Bao-qiang. Adaptive TM-CFAR Detection Based on the Statistics ODV[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2013, 36(2): 64-69.

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基于统计量ODV的自适应TM-CFAR检测

Adaptive TM-CFAR Detection Based on the Statistics ODV

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