Probabilistic Multi-Hypothesis Tracking 论文

详细信息

发表日期

1995-02-15

发表年份

1995

摘要

Abstract : In a multitarget, multimeasurement environment, knowledge of the measurement-to-track assignments is typically unavailable to the tracking algorithm. This study is a probabilistic approach to the measurement-to-track assignment problem. Measurements are not assigned to tracks as in traditional multi-hypothesis tracking (MHT) algorithms; Instead, the probability that each measurement belongs to each track is estimated using a maximum a posteriori (MAP) method. These measurement-to-track probability estimates are intrinsic to the multitarget tracker called the probabilistic multi-hypothesis tracking (PMHT) algorithm. The PMHT algorithm is computationally practical because it requires neither enumeration of measurement-to-track assignments nor pruning. The PMHT algorithm is an optimal MAP multitarget tracking algorithm. (AN)