摘要
建立了两站基于角度(DOA)和时差(TDOA)信息的伪线性观测模型,基于该模型提出了匀速运动目标的伪线性卡尔曼滤波(PLKF)算法。仿真结果表明该算法的稳健性要高于扩展卡尔曼滤波(EKF)算法,当观测误差较小时,PLKF算法的定位精度要高于EKF算法;当观测误差较大时,其定位精度低于EKF算法。对此文中结合两种算法的优点,提出了改进算法,以同时提高算法的定位精度和稳健性。
A pseudo-linear kalman filter（PLKF） algorithm was presented for tracking a moving target by using DOA and TDOA measurements based on two stations. The computer simulations show that the robustness of PLKF is higher then that of extended kalman filter（EKF） , for lower measurement errors the location accuracy of PLKF is better than that of EKF, but is somewhat worse when the measurement errors is larger. By combining PLKF with EKF, an improved algorithm is presented,which can improve the location accuracy and stability.
出处
《信号处理》
CSCD
北大核心
2008年第2期254-258,共5页
Journal of Signal Processing
