摘要
针对分布式雷达目标检测跟踪时传统方法存在的鲁棒性较差、运算复杂度较高等问题,该文提出了一种基于模糊贴近度函数的分布式无人机载雷达点迹自适应融合算法。该算法利用模糊贴近度函数对每部雷达的点迹质量进行评估,依此进行权重的自适应分配与点迹融合,能够有效提升点迹融合质量和效率,进而改进分布式无人机载雷达点迹融合与滤波跟踪的效果。仿真实验结果表明,所提算法的计算时间为1.4224 s,融合均方根误差为5.0202 m,融合后跟踪滤波均方根误差为4.4588 m,即运算复杂度、融合精度以及滤波跟踪精度均优于传统算法,具有较好的实用性和工程应用价值。
Aiming at researching and analyzing the problems of poor robustness and high arithmetic complexity that exist in the traditional methods of distributed radar target detection and tracking,a distributed unmanned airborne radar point track adaptive fusion algorithm based on the fuzzy nearness function is proposed.The algorithm utilizes the fuzzy nearness function to evaluate the trace quality of each radar,and then carries out the adaptive allocation of weights and trace fusion accordingly,which can effectively improve the quality and efficiency of trace fusion,and then improve the effect of trace fusion and filter tracking of distributed unmanned airborne radar.The simulation results show that the computation time of the proposed algorithm is 1.4224 s,the root mean square error of fusion is 5.0202 m,and the root mean square error of tracking filter after fusion is 4.4588 m,which means that the computational complexity,fusion accuracy,and filter tracking accuracy are all better than that of the traditional algorithms,and it has better practicality and engineering application value.
作者
周岩松
王伟
张俊
ZHOU Yansong;WANG Wei;ZHANG Jun(Xi’an Electronics and Engineering Research Institute,Xi’an 710100,China)
出处
《电子设计工程》
2025年第4期47-52,共6页
Electronic Design Engineering
