密集杂波环境下的数据关联快速算法

基于联合概率数据互联（JPDA）的思想，提出了一种新的数据关联快速算法（Fast Al-gorithm for Data Association,简称FAFDA算法）.该方法不需象在最优JPDA算法中那样生成所有可能的联合互联假设，因而具有计算量小，易于工程实现的特点。仿真结果表明，与最优JPDA算法相比，FAFDA算法的跟踪性能令人满意，并且在密集杂波环境下可实时、有效地跟踪100批次以上的目标。

FAST ALGORITHM FOR DATA ASSOCIATION IN DENSE CLUTTER

In multitarget tracking in clutter, often there are more than concerned measurement available for updating the state of a signal target. To solve the problem of data association between targets and measurements, a fast algorithm is proposed for data association in dense clutter based on the principle of joint probabilistic data association(JPDA). This algorithm is more efficient to directly compute a posterior probabilities without generating the data association hypotheses. The simulation results show that the computational cost for data association of the fast algorithm is significantly reduced than that of JPDA, and the tracking performance is very good in the case of more than 100 targets in dense clutter.