基于UKF的自适应网格交互式多模型算法

Adaptive Grid Interacting Multiple Model Algorithm Based on UKF

针对非线性观测条件下的机动目标跟踪问题,基于机动目标的协同转弯(CT)模型,采用无迹卡尔曼滤波(UKF)方法和自适应网格(AG)的模型集自适应策略,研究了一种变结构交互式多模型算法,即基于UKF的自适应网格交互式多模型(UKF-AGIMM)算法。对二维机动目标跟踪的仿真结果表明,本算法与相应的固定结构交互式多模型算法相比,可以解决固定结构多模型算法存在的问题,有效提高多模型算法的精度和费效比,缩短计算时间,且适合工程应用。

Devoted to the problem of maneuvering target tracking under nonlinear observation, a variable structure multiple model （ VSMM） algorithm called unscented Kalman filtering and adaptive grid interacting multiple model（ UKF-AGIMM） is developed in this paper, which is based on the coordinated turn （ CT） models, unscented Kalman filtering （ UKF） method and model set adaptive strategy of adaptive grid （ AG） . Simulation results show that this algorithm can solve the problems of fixed structure multiple model （ FSMM） algorithm, effectively improve the accuracy and cost-efficiency ratio of the multiple model algorithm, reduce the computation time in contrast to corresponding fixed structure algorithm, and is suitable for engi-neering applications.