当前统计模型自适应滤波算法改进

摘要

Due to the "current" statistical model adaptive filtering algorithm excessive dependence the maximum acceleration,so that it does not have higher tracking precision for the weak maneuvering target.Based on the research of "current" statistical model adaptive filtering algorithm and the analysis of the target tracking performance,it is proposed that the target maneuvering state can be divided into strong maneuvering and low weak maneuvering.When the target do weak maneuvering,a new method is proposed to improve tracking accuracy by correction maximal acceleration.Through the mathematical simulation of respectively on constant velocity,constant acceleration and weak variable accelerated.The simulation results show that through the method of correction maximum acceleration,can make filtering algorithm tracking accuracy for weak maneuvering target greatly improved.%由于“当前”统计模型自适应滤波算法对于最大加速度的过分依赖,使其对于弱机动目标并不具有较高的跟踪精度,基于“当前”统计模型自适应滤波算法的研究及目标跟踪性能的分析,提出了将目标的机动状态划分为强机动和弱机动,当目标在作弱机动运动时,可通过修正最大加速度来提高跟踪精度,分别针对常速、常加速、弱变加速三种弱机动情况进行了数学仿真,仿真结果表明,通过修正最大加速度的方法,可使该算法对于弱机动目标的跟踪精度大大提高.