基于IMM-RUASFF的网络化目标跟踪算法

针对目前网络化目标跟踪算法存在实时性差、精度低等问题进行了研究。首先,基于网络信息共享需求,建立了网络探测节点的目标跟踪模型;其次,网络探测节点目标跟踪需求和实战要求发现目标经常是有多种运动状态并存,而单一模型的滤波器不能满足对机动目标跟踪性能的要求,采用了基于交互式多模型(Interacting Multiple Model,IMM)的有反馈实时更新的异步状态融合算法。最后,针对多个探测节点目标跟踪的状态融合估计问题,提出了一种有反馈实时更新的异步状态融合算法,通过仿真验证了算法的有效性。

Networked-attack Target Tracking Based on IMM-RUASFF Algorithm

The dissertation aimed at the low practicality and accuracy of Target tracking of networked. Firstly,Target tracking model of networked detectional node is build based on network information sharing requirement;Secondly,Based on Interacting Multiple Model (IMM) Real-time Updated Asynchronous State Fusion with Feedback (RUASFF) is used for target tracking state estimation of detection node and the actual combat requirement,which find the target motion state is often a variety of coexistence,the filter can't meet the single model for maneuvering target tracking performance requirements. Finally,Real -time updated asynchronous state fusion with feedback (RUASFF) is proposed for target tracking of multiple detection nodes,and the effectiveness of the algorithm is verified by simulation.