模型参数自适应的交互多模强跟踪算法

Interacting Multiple Model STF Algorithm with Adaptive Model Parameters

基于强跟踪滤波器对突变状态的良好跟踪能力,设计了一种自适应交互多模算法。在交互多模算法框架内,计算"当前"统计模型的概率和目标机动强度信息(由残差统计距离来表征),自适应地调整"当前"统计模型的加速度等参数,提高了"当前"统计模型的自适应性和滤波器的鲁棒性,增强了系统对目标突发强机动的跟踪能力。仿真结果验证了该算法的有效性。

Based on the fine performance of STF filter to mutations, an adaptive interacting multiple model STF algorithm is designed. In the frame of interacting multiple model algorithm, the ＂current＂ probability of statistic model and information of target maneuvering intensity （represented by statistic residual distance） are calculated to adjust ＂current＂ parameters of acceleration velocity of statistic model adaptively. Thus, the adaptability of ＂current＂ Statistic model and robustness of filter are improved and the STF performance to sudden maneuver of target is enhanced. Simulation proves the validity of this algorithm.