改进的多传感器多目标量测数据关联算法

Improved Measurement Data Association Algorithm of Multi-sensor Multi-Target System

提出融合多传感器测量对目标位置进行估计的广义概率数据关联(MSPE-GPDA)算法.首先对所有可能的多元量测组合进行预关联检验,通过检验的有效多元量测组合所对应的目标位置进行最优估计;根据广义概率数据关联算法计算通过预关联检验的各有效量测组合与目标航迹间的关联概率,并用来计算目标的更新状态.与顺序处理的多传感器广义概率数据关联算法和利用多传感器量测进行目标位置估计的联合概率数据关联算法相比,MSPE-GPDA算法集中了最优估计和有效信息复用两方面的优点.理论分析与仿真实验结果均验证了所提算法的有效性.

A generalized probabilistic data association algorithm fusing measurements of multi-sensor to estimate the position of target is proposed.Firstly,the algorithm implements pre-correlation statistical test on all possible multi-tuple of measurement,and estimates the target＇s position that the valid multi-tuple of measurement which has passed through the pre-correlation statistical test corresponds to.Then the association probability between the valid measurement and target track is calculated according to generalized probabilistic data association algorithm,and is further used to calculate the update state of target.In comparison with sequential processing of multi-sensor generalized probabilistic data association algorithm and joint probabilistic data association algorithm fusing measurements of multi-sensor to estimate the position of target,the new algorithm has the advantages of both the optimal estimate and effective reuse of information.Both theory analyses and simulation results have verified the effectiveness of the proposed algorithm.