ISSN: 1673-825X    Imprint: Chongqing University of Posts and Telecommunications Journal
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非均匀噪声环境下分布式IVI-CFAR检测算法
Distributed IVI-CFAR detection algorithm in non-homogenous environments
DOI:10.3979/j.issn.1673-825X.2019.04.011
Received:May 19, 2018  Revised:September 07, 2019
中文关键词:目标检测  恒虚警  分布式检测  VI-CFAR  非均匀噪声
英文关键词:target detection  constant false alarm rate (CFAR)  distributed detection  VI-CFAR  non-homogeneous environments
基金项目:国家重点研发计划项目(2017YFB0102600);安徽省自然科学基金(TSKJ2015B12);安徽省科技重大专项计划项目(16030901032);安徽省高等教育提升计划(TSKJ2016B06);安徽工程大学计算机应用技术重点实验室开放基金(JSJKF201514);安徽工程大学科技成果转化引导基金项目(2018一种低成本的车辆开门防撞预警系统);高校优秀青年人才支持计划重点项目(gxyqZD2019052)
Author NameAffiliationE-mail
WANGLulin College of Computer and Information Science, Anhui Polytechnic University, Wuhu 241000, P. R. China wanglulinswjtu@163.com 
LIU Guiru College of Computer and Information Science, Anhui Polytechnic University, Wuhu 241000, P. R. China liuguiru@ahpu.edu.cn 
ZOU Shan College of Computer and Information Science, Anhui Polytechnic University, Wuhu 241000, P. R. China  
LI Zhiling College of Computer and Information Science, Anhui Polytechnic University, Wuhu 241000, P. R. China  
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中文摘要:
      为了解决传统分布式VI-CFAR(variability index-constant false alarm rate)和OS-CFAR(order statistic constant false alarm rate)算法在多杂波干扰环境下检测性能严重下降的问题,提出了一种分布式IVI-CFAR(improved VI-CFAR)检测算法。在VI-CFAR的基础上,引入双参考窗和双参量,通过各子参考窗参量与对应门限的比较,判断子参考窗中参考单元的分布情况,从而选择相应的参考单元集和检测器估计背景噪声功率。经过仿真对比,在单杂波和多目标干扰环境下,分布式IVI-CFAR算法检测性能接近于分布式VI-CFAR和OS-CFAR算法;在多杂波干扰环境下,分布式IVI-CFAR算法检测性能优于分布式VI-CFAR和OS-CFAR算法,采用“OR”融合规则时,检测性能最优。结果表明,提出的分布式IVI-CFAR算法在非均匀噪声环境下,均具有较优的检测性能。
英文摘要:
      In order to solve the problem that the detection performance of the conventional distributed VI-CFAR and OS CFAR detectors degrade severely in multiple clutter environment. A distributed improved variability index (IVI-CFAR) detection algorithm is proposed. Based on VI-CFAR, a double reference window and two parameters are introduced. By comparing the sub-reference window parameters with the corresponding thresholds, the distribution of reference cells in the sub-reference window is determined, so that the corresponding reference cell set and detector are selected to estimate background noise power. Through the simulation comparison, distributed IVI-CFAR is close to distributed VI-CFAR and OS-CFAR in a single clutter edge and multi-interfering targets environments; distributed IVI-CFAR is superior to distributed VI-CFAR and OS-CFAR in multi-clutter edges environment. Especially, distributed IVI-CFAR with′OR′fusion rule presents the highest detection performance. The results show that the distributed IVI-CFAR algorithm has better detection performance in non-homogenous environments.
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