一种基于扩展Kalman滤波的多径估计算法

摘要

定位系统中,噪声环境下的多径估计是消除多径干扰的前提.提出了一种基于扩展Kalman滤波(EKF)的多径估计算法,可以有效的估计多径信号的时间延迟和幅度.分析了本地码估计偏差、EKF的估计初值、相关间距以及采样频率对多径估计性能的影响.结果表明,EKF在估计多径信号时,EKF初值不仅影响其收敛速度,而且EKF初值中的幅度初值决定其是否收敛.同时,EKF时间延迟估计误差可以通过提高采样频率和增加最大早晚码间距来减小.%In positioning system, multipath estimation in noisy environment is the precondition of multipath elimination. A multipath estimation algorithm based on extended Kalmna filter was proposed, which can estimate the multipath time delay and multipath amplitude effectively. The influence of estimation error of local code, the initial value of extended Kalman filter (EKF) , the correlator spacing and the sampling frequency was analyzed in this paper. The simulation results show that the initial value of EKF influenced the convergence rate, and the amplitude value in initial value determined the convergence of EKF. Furthermore, the estimation error of multipath time delay was reduced by increasing sampling frequency and the maximum early-late spacing of local code.