一种机动目标多假设跟踪方法

A Novel Multiple Hypothesis Tracking Method for Maneuvering Target Tracking

提出了一种基于交互式多模型(IMM)的基于最大权重独立集的多假设(MWIS-MHT)方法;将IMM算法引入到MWIS-MHT框架中,采用多种运动模型对机动目标进行跟踪,通过半-马尔科夫过程生成的多机动目标场景对所提方法进行了验证,实验结果表明:所提方法能有效提升目标跟踪的连续性和状态估计的精度,兼顾了MWIS-MHT在计算效率上的优势。相比于MWIS-MHT方法,所提方法更适用于多机动目标的跟踪场景。

In order to overcome the problem that the existing maximum weighted independent set based MHT(MWIS-MHT)methods are not suitable for multiple maneuvering targets tracking problem,a novel MWIS-MHT method based on the interracting multiple model(IMM)algorithm is proposed.The proposed method introduce the IMM algorithm into the MWIS-MHT structure,thus it exploits multiple motion models to track maneuvering targets.In addition,the proposed method method can take into account the advantages of MWIS-MHT in terms of computational efficiency.The multi-maneuver target scene generated by the semi-Markov process was used to verify the proposed method.The experimental results show that the proposed method can effectively improve the continuity of target tracking and the accuracy of state estimation.Therefore,compared with the MWIS-MHT method,the proposed method is more suitable for tracking scenarios of multiple maneuvering targets.