机动目标跟踪的自适应相互作用多模型算法
Interacting multiple model algorithm in target tracking
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摘要: 针对目标跟踪中的目标机动问题提出了一种“基于自适应相互作用多模型”的算法。使用不同的几个子模型来描述目标的运动状态，各个模型有自己的随目标估计状态和当前测量值变化的模型概率,并且各模型之间能通过马尔可夫链的控制自动平滑切换。仿真实验表明了该算法能很好地适应目标的机动，即使采用两个子模型来描述目标的运动，跟踪精度也比较好。Abstract: In order to resolve the maneuvering problem in target tracking, an algorithm based on interacting multiple model(IMM) method was presented. In this method every sub-model has its own model match probability that changes with the target's estimated state and measures. The sub-model can soft-jump between each other under the control of Markovian switching coefficients. From simulation it can be seen that the IMM method can improve the tracking accuracy of maneuvering targets.
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