【摘要】 首先研究了基于粗关联和精关联过程的多传感器多目标 (MSMT)跟踪融合算法 ,精关联是联合概率数据关联 (JPDA)算法的推广 ,JPDA算法存在随传感器数和目标数的增加而计算量迅速增加的缺点 ;其次提出了一种基于神经网络的MSMT联合概率数据互联 (MNJPDA)算法 ,MNJPDA算法能克服计算量爆炸问题 ,基于MNJPDA的融合算法能提高跟踪的快速性 .仿真结果证明了MNJPDA融合算法的有效性更多还原

【Abstract】 A fusion algorithm in multisensor multitarget (MSMT) tracking based on rough association and precise association is studied. The method of precise association is an extension of join probabilistic data association (JPDA) algorithm. The shortcoming of JPDA algorithm is that the computation load would increase evidently with the increase of sensor number and target number. A new multisensor multitarget JPDA algorithm based on neural network, named MNJPDA, is proposed. The MNJPDA algorithm can overcome the problem of expansion of computation load in MSMT tracking. The MNJPDA fusion algorithm can improve the tracking speed. The simulation results show the MNJPDA fusion algorithm is valid.更多还原