论文标题
使用总产品算法进行分类的多坐Multitarget跟踪
Classification-Aided Multitarget Tracking Using the Sum-Product Algorithm
论文作者
论文摘要
Multitarget跟踪（MTT）是一项具有挑战性的任务，旨在从一个或多个传感器提供的目标状态测量中估算目标及其状态的数量。其他信息，例如分类器提供的目标类别的不完善估计，可以促进目标测量关联，从而提高MTT性能。在这封信中，我们描述了如何将基于总和算法的最近提出的MTT框架扩展到有效利用类信息。通过模拟结果证明了所提出的方法的有效性。
Multitarget tracking (MTT) is a challenging task that aims at estimating the number of targets and their states from measurements of the target states provided by one or multiple sensors. Additional information, such as imperfect estimates of target classes provided by a classifier, can facilitate the target-measurement association and thus improve MTT performance. In this letter, we describe how a recently proposed MTT framework based on the sum-product algorithm can be extended to efficiently exploit class information. The effectiveness of the proposed approach is demonstrated by simulation results.
