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针对机动目标跟踪问题,基于转换时间条件交互多模型(STC-IMM)结构,提出一种转换概率自适应的STC-AIMM算法.该算法根据滤波器收敛时间预设了模型转换时间条件,保证了滤波器对目标后验状态的合理逼近,同时通过模型转换概率的自适应算法实现了模型与目标运动模式的实时最优匹配.理论和仿真分析结果表明:相比交互多模型(IMM)算法和STC-IMM算法,该算法能够发挥滤波器最优性能,实现模型概率的优化分配,对目标不同强度的机动具有良好的适应性、跟踪稳定性和更高的跟踪精度.
In order to solve the maneuvering target tracking problem, an STC-AIMM algorithm is proposed based on STC-IMM, which is based on the STC-IMM algorithm. This algorithm presets the model switching time according to the filter convergence time, Filter approximating the posteriori positve state of the target and the real-time optimal matching between the model and the target motion mode is realized through the adaptive algorithm of model transition probability.The theoretical and simulation results show that compared with the IMM algorithm and STC-IMM algorithm, the algorithm can optimize the performance of the filter to achieve the optimal distribution of the model probability, and has good adaptability, tracking stability and tracking accuracy to different maneuvering targets with different intensities.