改进模糊综合评价的ESM与雷达航迹关联算法  

An ESM-Radar Track Correlation Algorithm Based on Improved Fuzzy Comprehensive Evaluation

作　　者：张肖强[1] 王星[1] 周东青[1] 杜文红[1] 于媛[1] 

机构地区：[1]空军工程大学航空航天工程学院,西安710038

出　　处：《空军工程大学学报（自然科学版）》2017年第1期44-49,共6页Journal of Air Force Engineering University(Natural Science Edition)

基　　金：航空科学基金(20152096019;20145596025)

摘　　要：针对机动目标贴近和交叉运动影响下的ESM与雷达的航迹关联问题,提出了基于改进的模糊综合评价的航迹关联算法。该算法综合考虑了ESM传感器和雷达在双机协同无源定位中获得的距离、角度、速度、相位差和时间差信息,丰富了模糊因素集;给出了模糊综合评价中的隶属度和权重的动态计算方法,并对评价集和评价准则进行了相应的改进。仿真结果表明,在目标距离200 m时,传统的多因素模糊综合决策航迹关联算法的关联正确率为55.2%,航迹关联算法的关联正确率为74.0%。在增大目标距离和雷达探测误差的情况下,算法的关联正确率始终高于传统的多因素模糊综合决策航迹关联算法。In order to solve ESM-radar track correlation problem under condition of the influence on the maneuvering target close and cross, this paper presents a track correlation algorithm based on the improved Fuzzy comprehensive evaluation. In consideration of distance, angle, speed, phase difference and time difference information of the ESM sensor and radar in the cooperative passive location, the algorithm enriches the fuzzy factor set, gives out a dynamic calculation method of membership degree and weight in fuzzy comprehensive evaluation, and correspondingly improves the evaluation set and the evaluation criterion. The simulation results show that when the target is at the distance of 200m, the traditional multi-factor fuzzy integration judgment algorithm＇s correlation accuracy is 55.2 %, and this paper＇s algorithm＇s correlation accuracy is 74.0%. Under condition of increasing the target distance and the radar detection error, this algorithm＇s correlation accuracy is always higher than that of the traditional multi-factor fuzzy integration judgment algorithm.

关 键 词：模糊综合评价 航迹关联 模糊因素 动态隶属度 雷达 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]