华东师范大学学报（自然科学版） >

2018 , Vol. 2018 >Issue 1: 135 - 145

DOI: https://doi.org/10.3969/j.issn.1000-5641.2018.01.013

物理学与电子学

非均匀噪声下基于双剔除门限的恒虚警[2mm]目标检测算法

  • 刘贵如 ,
  • 王陆林 ,
  • 邹姗
展开
  • 1. 安徽工程大学 计算机与信息学院, 安徽 芜湖 241000;
    2. 奇瑞汽车股份有限公司 前瞻技术研究院, 安徽 芜湖 241006
刘贵如,女,硕士,副教授,研究方向为信号处理、车辆主动安全和多传感器融合.E-mail:liuguiru_yunnan@163.com.

收稿日期: 2016-09-14

  网络出版日期: 2018-01-11

基金资助

国家自然科学基金（91120307）；安徽省自然科学基金（TSKJ2015B12）；安徽工程大学计算机应用技术重点实验室开放基金（JSJKF201514）

收起

CFAR target detection algorithm based on dual-censoring threshold in non-homogeneous environments

  • LIU Gui-ru ,
  • WANG Lu-lin ,
  • ZOU Shan
Expand
  • 1. College of Computer and Information Science, Anhui Polytechnic University, Wuhu Anhui 241000, China;
    2. Prospective Technology Research Institute, Chery Automobile Co., Ltd, Wuhu Anhui 241006, China

Received date: 2016-09-14

  Online published: 2018-01-11

Fold

摘要

为了解决雷达检测算法在非均匀噪声环境下目标检测性能严重下降的问题，在分析实际回波杂波分布特性的基础上，提出了一种基于双剔除门限的恒虚警目标检测算法，通过双剔除门限将极大极小干扰信号从参考窗口中剔除，实时精确估计背景噪声功率.经过与各检测算法仿真对比，该算法在多目标干扰、遮挡和杂波边缘干扰等非均匀背景噪声环境下仍具有最优的检测性能和鲁棒性.结果表明，所提出的目标检测算法在非均匀噪声环境下具有良好的检测性能.

关键词： 目标检测; 恒虚警; 双门限检测; 非均匀噪声

本文引用格式

刘贵如 , 王陆林 , 邹姗 . 非均匀噪声下基于双剔除门限的恒虚警[2mm]目标检测算法[J]. 华东师范大学学报（自然科学版）, 2018 , 2018(1) : 135 -145 . DOI: 10.3969/j.issn.1000-5641.2018.01.013

Abstract

In order to solve the problem that the detection performance of the radar target detector decreases badly in non-homogeneous environments. Based on the actual echo clutter distribution, a dual-censoring threshold constant false alarm rate (DCT-CFAR) detector is proposed. Dual censoring threshold is used to remove the large and small unwanted samples and real-time accurate estimate the background noise power level. Compared with the simulation and analysis results of other detectors, the proposed detector has the best detection performance and stability in multi-interfering targets, masking effect, clutter edge and other non-homogenous environments. The results show that the proposed detector still has a good detection performance in non-homogeneous environments.

Key words： target detection; constant false alarm rate (CFAR); dual threshold detection; non-homogenous noise

参考文献

[1] 章建成, 苏涛, 吕倩. 基于运动参数非搜索高速机动目标检测[J]. 电子与信息学报, 2016, 6:1460-1467.
[2] 简涛, 苏峰, 何有, 等. 复合高斯杂波下距离扩展目标的自适应检测[J]. 电子学报, 2012(5):990-994.
[3] 刘红亮, 周生华, 刘宏伟, 等. 一种航迹恒虚警的目标检测跟踪一体化算法[J]. 电子与信息学报, 2016(5):1072-1078.
[4] 于洪波, 王国宏, 曹倩, 等. 一种高脉冲重复频率雷达微弱目标检测跟踪方法[J]. 电子与信息学报, 2015(5):1097-1103.
[5] SHTARKALEV B, MULGREW B. Multistatic moving target detection in unknown coloured Gaussian interference[J]. Signal Processing, 2015, 115:130-143.
[6] DU B, ZHANG L P. Target detection based on a dynamic subspace[J].Pattern Recognition, 2014, 47:344-358.
[7] LEI S W, ZHAO Z Q, NIE Z P, et al. Adaptive polarimetric detection method for target inpartially homogeneous background[J]. Signal Processing, 2015, 106:301-311.
[8] HOU H L, PANG C S, GUO H L, et al. Study on high-speed and multi-target detection algorithm based on STFT and FRFT combination[J]. Optik, 2016, 127:713-717.
[9] ZAIMBASHI A. An adaptive CA-CFAR detector for interfering targets and clutter-edge situations[J]. Digital Signal Processing, 2014, 31:59-68.
[10] MEZIANI H A, SOLTANI F. Optimum second threshold for the CFAR binary integrator in Pearson-distributed clutter[J]. Signal, Image and Video Processing, 2012(6):223-230.
[11] WEINBERG G V, KYPRIANOU R. Optimised binary integration with order statistic CFAR in Pareto distributed clutter[J]. Digital Signal Processing, 2015, 42:50-60.
[12] BOUDEMAGH N, HAMMOUDI Z. Automatic censoring CFAR detector for heterogeneous environments[J]. AEU-Internationl Journal of Electronics and Communications, 2014, 68:1253-1260.
[13] ZAIMBASHI A, NOROUZI Y. Automatic dual censoring CA-CFAR detector in non-homogenous environments[J]. Digital Signal Processing, 2008, 88:2611-2621.
[14] MEZIANI H A, SOLTANI F. Decentralized fuzzy CFAR detectors in homogeneous Pearson clutter background[J]. Signal Processing, 2011, 91:2530-2540.
[15] SMITH M E, VARSHNEY P K. Intelligent CFAR processor based on data variability[J]. IEEE Transactions on Aerospace and Electronic Systems, 2000, 36(6):837-847.
[16] MATA-MOYA D, DEL-REY-MAESTRE N, PELÁEZ-SÁNCHEZ V M., et al. MLP-CFAR for improving co-herent radar detectors robustness in variable scenarios[J]. Expert Systems with Applications, 2015, 42(11):4878-4891.
[17] ZHANG R L, SHENG W X, MA X F, et al. Constant false alarm rate detector based on the maximal reference cell[J]. Digital Signal Processing, 2013, 23:1974-1988.
[18] FARROUKI A, BARKAT M. Automatic censoring CFAR detector based on ordered data variability for nonhomogeneous environments[J], IEEE Proc Radar Sonar Navig, 2005, 152:43-51.
[19] 关键, 张晓利, 简涛, 等. 分布式目标的子空间双门限GLRT-CFAR检测[J]. 电子学报, 2012, 9:1759-1764.
[20] 陈建军, 黄孟俊, 赵宏钟, 等. 相参雷达时频域CFAR检测门限获取方法研究[J]. 电子学报, 2013, 8:1634-1638.
[21] GURAKAN B, CANDAN C, CILOGLU T. CFAR processing with switching exponential smoothers for nonhomogeneous environments[J]. Digital Signal Processing, 2012, 22:407-416.
[22] WEINBERG G V. Management of interference in Pareto CFAR processes using adaptive test cell analysis[J]. Signal Processing, 2014, 104:264-273.
Options
文章导航

/

〈 〉