NLOS环境下基于TOA/AOA的单基站目标跟踪

现有的单基站定位技术由于非视距（Non-Line-of-Sight,NLOS）误差的存在，导致定位性能急剧下降。针对这一问题，提出了一种基于单基站的改进扩展卡尔曼滤波（Extended Kalman Filter,EKF）算法。该算法在扩展卡尔曼滤波器中引入阈值去判断是否丢弃测量值，通过对卡尔曼增益的处理来提高对NLOS误差的滤除能力，最后利用扩展卡尔曼滤波器的跟踪性能对移动目标进行定位跟踪。仿真结果表明，所提算法的定位精度优于传统的EKF、无迹卡尔曼滤波器（Unscented Kalman Filter,UKF）等算法，且对抑制NLOS误差具有良好的效果。

Single base station target tracking based on TOA/AOA in NLOS environment

Due to non-line-of-sight(NLOS) errors,the positioning performance of the existing single base station positioning technology drops sharply.Concerning this issue,an improved extended Kalman filter(EKF) algorithm based on a single base station is proposed.The threshold is introduced into the EKF to judge whether to discard measured values or not,and the filtering ability of NLOS error is improved by processing the Kalman gain.The tracking performance of the EKF is used to track the mobile target.The simulation results show that the positioning accuracy of the proposed algorithm is better than that of traditional EKF and Unscented Kalman Filter(UKF) algorithms,and it has a better performance in suppressing NLOS errors.