基于UKF的自适应网格交互式多模型算法

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

Adaptive Grid Interacting Multiple Model Algorithm based on UKF

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 engineering applications.