摘要
概率数据关联滤波器(PDAF)算法用于杂波环境下时,目标跟踪存在跟踪机动目标能力低,位置误差大,协方差也大等问题;为了解决这些问题,在PDAF算法的基础上,提出了定向概率数据关联滤波器(DPDAF)算法;在不改变PDAF滤波算法的情况下,通过引入目标预测的夹角,在PDAF中增加检测方向,通过修改PDAF的似然函数,从而得到DPDAF算法;最后通过计算机仿真,DPDAF算法跟踪机动目标的能力高于传统的PDAF算法,提高了算法的跟踪性能。
Probabilistic data association filter（ PDAF） algorithm is used to clutter environment,have problems such as low ability to track the maneuvering target tracking and the position error,covariance big etc. In order to solve these problems,on the basis of PDAF algorithm,proposed the directional probabilistic data association filter（ DPDAF） algorithm. Under the condition of without changing PDAF filter algorithm,by introducing the target angle prediction,increase in PDAF detection direction,by modifying the likelihood function of PDAF,DPDAF algorithm is obtained. At last,through computer simulation,DPDAF algorithm for tracking maneuvering target ability is higher than the traditional PDAF algorithm,improve the tracking performance of the algorithm.
出处
《工业仪表与自动化装置》
2016年第1期115-117,共3页
Industrial Instrumentation & Automation
基金
甘肃省财政厅
甘肃省科技厅科技支撑计划项目(甘财教[2011]82号-61)
