轨道聚结和排斥：MHT、JPDA和BP
Track Coalescence and Repulsion: MHT, JPDA, and BP
摘要：
联合概率数据关联（JPDA）和多假设跟踪（MHT）是70年代提出的两种多目标跟踪方法。在过去的几十年里，广泛的研究已经揭示了不良行为的JPDA和MHT类型的方法在跟踪场景中的目标非常接近。特别地，JPDA遭受径迹聚结效应，即，非常接近的目标的估计轨迹趋于合并并且可能变得不可区分。有趣的是，在MHT中，可以观察到与轨道聚结相反的效应，称为轨道排斥。在本文中，我们回顾了估计策略的MHT，JPDA，和最近推出的置信传播（BP）框架MTT，我们调查BP也遭受这两个不利影响。我们的数值结果表明，基于BP的MTT可以很好地避免轨道排斥和合并。
英文摘要：
Joint probabilistic data association (JPDA) and multiple hypothesis tracking (MHT) introduced in the 70s, are still widely used methods for multitarget tracking (MTT). Extensive studies over the last few decades have revealed undesirable behavior of JPDA and MHT type methods in tracking scenarios with targets in close proximity. In particular, JPDA suffers from the track coalescence effect, i.e., estimated tracks of targets in close proximity tend to merge and can become indistinguishable. Interestingly, in MHT, an opposite effect to track coalescence called track repulsion can be observed. In this paper, we review the estimation strategies of the MHT, JPDA, and the recently introduced belief propagation (BP) framework for MTT and we investigate if BP also suffers from these two detrimental effects. Our numerical results indicate that BP-based MTT can mostly avoid both track repulsion and coalescence.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
