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Integrated Bayesian Clutter Estimation with JIPDA/MHT Trackers

机译:集成JIPDA / MHT跟踪器的贝叶斯杂波估计

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摘要

Based on Poisson point processes, multitarget multi-Bernoulli processes, and set calculus, a Bayesian method is presented to estimate the nonhomogeneous clutter background while simultaneously tracking multiple targets. A major feature of the proposed approach is the seamless integration of clutter estimation with standard multitarget tracking algorithms like the multiple hypothesis tracker (MHT) and the joint integrated probabilistic data association (JIPDA) tracker by exploiting the association events and their probabilities constructed and calculated in standard multitarget tracking algorithms.
机译:基于泊松点过程,多目标多伯努利过程和集合演算,提出了一种贝叶斯方法来估计非均匀杂波背景,同时跟踪多个目标。所提出方法的主要特征是通过利用关联事件及其在中构建和计算的概率,将杂波估计与标准的多目标跟踪算法(例如,多假设跟踪器(MHT)和联合集成概率数据关联(JIPDA)跟踪器)无缝集成。标准的多目标跟踪算法。

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