摘要
针对多种机动策略实时机动目标,为解决标准交互式多模型(IMM)算法的模型集冗余、算法量过大和实时性不高等问题,以提高机动目标滤波精度,保证目标跟踪系统性能,对基于模糊自适应理论的交互式多模型算法进行了研究。对标准IMM算法改进包括加速度预估、模型集合设计、模糊自适应推理设计,以及条件滤波输出四部分,通过加速度预估获得更准确的模型集,采用提前模型筛选获得更优的匹配效果并减少了计算量。给出了处理模型及滤波过程流程。对三维机动目标的仿真结果表明:与标准IMM算法相比,设计的基于滤波算法对以多种机动策略实时机动的目标有更好的实时性和跟踪性能。
For solving the disadvantages of model set redundancy,massive computation and low real-time to improve the filtering accuracy of maneuvering target and guarantee the performance of tracking system,the interacting multiple model（IMM）approach based on the fuzzy adoptive theory was studied for multiple maneuvering targets in this paper.The improved algorithm included four parts which were acceleration estimation,model set design,fuzzy adoptive reasoning design and conditional filtering output.The more accuracy model set was acquired by acceleration estimation.The better matching and less computation were gained by advanced model screening.The computation mode and flowchart were presented.The simulation results of 3D maneuvering target showed that the IMM approach in this paper had better real time and tracking performance than the standard IMM algorithm for multiple maneuvering targets.
出处
《上海航天》
2016年第2期43-47,共5页
Aerospace Shanghai
关键词
多策略机动目标
运动模型
交互式多模型
模糊理论
加速度预估
模型集合
自适应推理
条件滤波
实时性
Multiple maneuvering target
Motion models
Interacting multiple model
Fuzzy theory
Acceleration estimation
Model set
Adoptive reasoning
Conditional filtering
Real-time
