基于粒子滤波的模型自适应机动目标跟踪算法

针对当前机动目标跟踪领域中多模型算法存在的问题,提出一种基于粒子滤波的模型自适应机动目标跟踪算法.首先,依据前一时刻每个粒子采用的模型状态和模型间的状态转移概率,实现对当前时刻模型的采样;然后,将采样模型用于对当前粒子的预测,并根据当前时刻得到的量测数据实现对预测粒子权值的度量;最后,通过重采样策略和概率最大化原则完成对模型的合理选择和状态的有效估计.仿真实验验证了该算法的有效性.

Model adaptive maneuvering target tracking algorithm based on particle filtering

Aiming at the existing problems of current multi-model algorithm for maneuvering target tracking,the paper proposes a model adaptive maneuvering target tracking algorithm based on particle filtering.Firstly,the algorithm achieves the sampling for current moment model according to the previous moment particle model information and the model transfer probability.Then,the prediction for current particle is accomplished by combining the model sampling result with state transfer equation,and the weight of predic...