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多传感器多目标联合概率数据关联研究
引用本文:孙俊生,王建民,王维锋.多传感器多目标联合概率数据关联研究[J].无线电工程,2009,39(11):19-21.
作者姓名:孙俊生  王建民  王维锋
作者单位:中国人民解放军装甲兵工程学院,北京,100072
摘    要:联合概率数据关联(JPDA)算法对单传感器多目标跟踪是一种良好的算法,但对于多传感器密集多目标跟踪,则计算量剧增,数据关联成功率下降。因此,改进联合概率数据关联(AJPDA)算法对多传感器多目标量测进行同源划分及单一传感器测量数据转换,然后采用JPDA算法求解空间目标轨迹交叉时的数据关联。仿真结果表明,AJPDA算法提高了成功关联概率,降低了求解数据关联概率的难度,可以解决密集目标的正确跟踪问题。

关 键 词:多传感器多目标跟踪  联合概率数据关联  AJPDA算法

Research on Joint Probabilistic Data Association Algorithm for Multisensor-multitarget Tracking
SUN Jun-sheng,WANG Jian-min,WANG Wei-feng.Research on Joint Probabilistic Data Association Algorithm for Multisensor-multitarget Tracking[J].Radio Engineering of China,2009,39(11):19-21.
Authors:SUN Jun-sheng  WANG Jian-min  WANG Wei-feng
Affiliation:( The Armored Force Engineering Institute, Beijing 100072, China )
Abstract:The joint probabilistic data association (JPDA) algorithm is a good method for the single sensor muhitarget tracking. However, for the muhisensor-muhitarget (MSMT) tracking in clutter, its calculation load comes higher and it may cause the incorrect association data. Therefore, the amended joint probabilistic data association (AJPDA) algorithm for MSMT tracking is proposed in this paper. The same source observations are classified into the same set. Then the JPDA algorithm can be used to obtain the data association when the space target traces crossing. The simulation results show that the AJPI)A algorithm can increase the successful rate of data association, and reduce calculation complexity. This algorithm can make the sensor correctly track densely distributed targets.
Keywords:multisensor-muhitarget (MSMT) tracking  joint probabilistic data association (JPDA)  amended joint probability data association algorithm (AJPDA)
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