机动目标无源跟踪IMM-MKF算法

Maneuvering Target Tracking Algorithm Based on IMM-MKF

为提高运动多站对机动目标的无源跟踪性能,提出了一种新的基于交互式多模型-边缘化卡尔曼滤波(IMM-MKF)的机动目标跟踪算法。该算法将交互式多模型(IMM)结构和边缘化卡尔曼滤波(MKF)结合,利用MKF算法对每个模型进行滤波,对滤波结果进行交互作用来得到跟踪结果。以只测角机动目标跟踪为例对所提算法进行仿真分析,仿真结果表明,相对于采用扩展卡尔曼滤波(EKF)、不敏卡尔曼滤波(UKF)及容积卡尔曼滤波(CKF)算法的典型交互式多模型算法,所提算法具有更好的跟踪性能。

Aiming at improving the maneuvering target tracking performance using moving multiple pas-sive observer,a novel algorithm based on the interacting multiple model-marginalized Kalman filter（IMM-MKF）is proposed.The proposed algorithm combines the IMM with the MKF,which uses the MKF as the filter for each model and then the tracking results can be got by interacting effect with respect to the filtering results.The bearings-only maneuvering target is taken as an example to test the performance of the proposed algorithm.The simulation results indicate that the proposed algorithm has improved tracking performance, compared to typical IMM algorithms which use filters such as the extended Kalman filter（EKF）,the un-scented Kalman filter（UKF）and the cubature Kalman filter（CKF）.