针对利用传统算法难以跟踪低空目标的问题,提出了一种可行的跟踪低空目标的最大似然-概率数据关联(ML-PDA)算法。在分析各种低空目标特性的基础上,首先建立了基于ML-PDA滤波算法的低空目标跟踪模型,然后对该模型进行了深入分析,最后通过计算机仿真对该模型进行了验证。结果表明:ML-PDA滤波算法对低空目标跟踪十分有效,并且提高了滤波实时性,具有较好的工程应用前景。

In view of existing problems in traditional algorithm applied in tracking low observable targets, a feasible ML-PDA algorithm was proposed. On the basis of characteristic analysis of low-attitude target, firstly, the tracking for low observable targets was built based on ML-PDA algorithm. Then, this model was analyzed deeply and finally this model was validated through computer simulation. The simulation results show that ML-PDA algorithm is effective on trackig low-attitude observable targets, the method has a good prospect in engineering application.