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首页> 外文会议>Conference on Signal and Data Processing of Small Targets 2002, Apr 2-4, 2002, Orlando, USA >Bayesian approach to avoiding track seduction
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Bayesian approach to avoiding track seduction

机译：避免轨道吸引的贝叶斯方法

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摘要

The problem of maintaining track on a primary target in the presence spurious objects is addressed. Recursive and batch filtering approaches are developed. For the recursive approach, a Bayesian track splitting filter is derived which spawns candidate tracks if there is a possibility of measurement misassociation. The filter evaluates the probability of each candidate track being associated with the primary target. The batch filter is a Markov-chain Monte Carlo (MCMC) algorithm which fits the observed data sequence to models of target dynamics and measurement-track association. Simulation results are presented.
机译：解决了在存在伪造对象中在主要目标上保持跟踪的问题。开发了递归和批处理过滤方法。对于递归方法，派生出贝叶斯磁道分割滤波器，如果存在测量失配的可能性，则产生候选磁道。过滤器评估每个候选轨道与主要目标相关联的可能性。批处理过滤器是马尔可夫链蒙特卡洛（MCMC）算法，它使观察到的数据序列适合目标动力学和测量轨迹关联的模型。给出了仿真结果。

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