具有模型概率修正的新颖IMMPDA算法

Novel IMMPDA algorithm with model probability correction

为了有效提高杂波环境中机动目标跟踪的精度,将标量交互式多模型(SIMM)算法与概率数据关联(PDA)算法结合成SIMMPDA算法。其中,PDA算法能够有效处理杂波环境下的数据关联与测量不确定性。SIMM算法处理运动模型间的切换,且在线性最小方差意义下获得目标的最优状态估计。而考虑因杂波的干扰导致各时刻的匹配模型占优程度不明显的问题,故再对各时刻SIMMPDA算法所得的后验模型概率进行修改,得到一个基于模型概率修改的SIMMPDA算法,即为M-SIMMPDA算法。仿真结果表明,所提算法的跟踪精度得到一定程度的提高。

The probability data association（PDA） algorithm is incorporated with scalar interactive multiple model （SIMM） to form SIMMPDA algorithm in order to improve tracking precision of maneuvering target in clutter environment. The PDA algorithm handles data association and measurement uncertainties in clutter environment. The SIMM algorithm deals with the model switching and obtain the optimal state estimations of target in the linear minimum variance sense. In consideration of the problem that the matched model hasn~ dominance obvious due to the interference of clutter at each time, so that the model probability of the SIMMPDA algorithm is modified. Thus, a M-SIMMPDA algorithm,which is a SIMMPDA algorithm based on model probability modification is presented. The simulation results show that the tracking precision of the proposed algorithm has been improved to some extent.