关键词: 目标跟踪, 交互多模型, 自适应变结构, 信息滤波, 无迹卡尔曼滤波

Abstract: Most current maneuvering target tracking algorithms use Interacting Multiple Model （IMM） by switching fixed models, which can easily cause problems like model-mismatching and thus resulting in inaccurate tracking. Meanwhile, multiple sensors are now generally available to provide multi-measurements for target tracking, provoking the needs to efficiently utilize them. To solve these problems, a new algorithm that consists of less models and integrates adaptive Variable Structure Multi-Model （VSMM） and Information Filtering （IF） is presented, which accomplishes better estimation of maneuvering target’s trajectory through updating the model-set’s parameters in real time and fusing multi-measurements by unscented Kalman IF. Simulation results prove that this new algorithm can efficiently fuse multi-measurements, adaptively match target’s real model and reach a high level of target tracking.

Key words: target tracking, Interacting Multiple Model（IMM）, adaptive variable structure, information filtering, Unscented Kalman Filtering（UKF）