摘要
为提高组网雷达的分布式恒虚警(constant false alarm rate, CFAR)检测性能,基于模糊逻辑和最大选择筛选平均检测器(maximum-censored mean level detector, MX-CMLD)提出一种自适应多传感器分布式模糊CFAR检测算法。该方法是一种基于无信噪比信息的检测融合算法,通过传输单部雷达站接收信号的检验统计量、检测可信度来完成全局的CFAR检测。该方法通过表决模块和反馈模块,控制传输到融合中心的数据量,并自适应选取相关的雷达数据进行融合,在一定程度上可以实现雷达资源的管理。仿真结果表明,在均匀背景、多目标干扰背景的目标检测中,自适应分布式模糊MX-CMLD均有较好的检测性能。
In order to improve the performance of constant false alarm rate(CFAR) detection of netted radar, based on fuzzy logic and maximum-censored mean level detector(MX-CMLD), an adaptive multi-sensor distributed fuzzy CFAR detection algorithm is proposed, which is a detection fusion algorithm based on no signal to noise ratio information. The CFAR detection is completed by transmitting the test statistics and detection reliability of the received signal of a single radar station. This method controls the amount of data transmitted to the fusion center through the voting module and feedback module, and adaptively selects the relevant radar data for fusion, which can achieve the management of radar resources to a certain extent. Simulation results show that the adaptive distributed fuzzy MX-CMLD has better detection performance in the background of uniform and multi-target interference.
作者
龚树凤
龙伟军
贲德
潘明海
GONG Shufeng;LONG Weijun;BEN De;PAN Minghai(College of Information Engineering,Zhejiang University of Technology,Hangzhou 310012,China;Nanjing Research Institute of Electronics Technology,Nanjing 210038,China;College of Electronic and Information Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China)
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2022年第1期100-107,共8页
Systems Engineering and Electronics
基金
浙江省教育厅科研项目(Y201839636)
国家自然科学基金(61671241,62071440)资助课题。
