摘要
针对卡尔曼滤波对3GPP长期演进(LTE,long term evolution)终端非合作跟踪定位精度较差的问题,提出了基于非合作定位模型的改进型粒子滤波算法。该算法以侦测站从空口截获的含有噪声的波达时延差(TDOA)和波达时延和(TSOA)信息为基础,建立目标跟踪定位模型,通过改进型粒子滤波(PF,particle filter)算法实现对目标终端的位置和速度的跟踪获取。仿真实验表明,该算法可以有效实现对目标的跟踪,较无迹卡尔曼滤波(UKF,unscented kalman filter)算法有更好的准确性。
In order to solve the poor accuracy problem of non-cooperative target tracking by the algorithm of Kalman filter in LTE, this paper offered the model of non-cooperative target tracking This algorithm built a target tracking model which based on the TDOA and TSOA inforrmtion. These information were intercepted by monitoring station from the spatial interface the target tracking by a advanced particle filter was realized. Numerical simulations showed that the algo- rithm could realize the target tracking and bad a better veracity than UKF.
出处
《探测与控制学报》
CSCD
北大核心
2015年第4期72-76,共5页
Journal of Detection & Control
基金
国家自然科学基金项目(61272333)
安徽省自然科学基金项目(1208085MF94)