基于自适应EKF的弱GNSS信号跟踪算法

Weak GNSS Signal Tracking Algorithm Based on  Adaptive Extended Kalman Filter[HS)]

摘要:

弱GNSS信号跟踪技术是卫星导航接收机关键技术之一,跟踪技术的好坏将直接影响卫星导航接收机在弱信号条件下的跟踪性能;在动态环境和先验信息不充分的情况下,由于扩展卡尔曼滤波(EKF)的固定设计使其不能满足要求,针对此不足引入一种自适应扩展卡尔曼滤波(AEKF)的信号跟踪算法;该自适应滤波算法能够实时监测残差或滤波器新息的动态变化,来修正观测噪声方差和状态噪声方差,以此调整滤波器增益,观测值和控制预测值在滤波结果中的权重;理论分析和结果表明,该算法能够充分利用观测信号的统计特性,克服了传统EKF算法不足,获得更好的跟踪性能。

Abstract:

Weak GNSS signal tracking technology is one of the key technology of satellite navigation receiver, tracking technology will directly affect the performance of the satellite navigation receiver in weak signal conditions. Because the traditional extended Kalman filter (EKF) has some limitations in dynamic environments with insufficient priori information, this paper proposed a signal tracking algorithm based on adaptive extended Kalman filter (AEKF). This adaptive filter monitors the changes in innovations or residuals to correct the process and measurement noise covariances, and then adjusts the filter gain to control the wights between the predicted values and observed values in the filter results. Theoretical analysis and simulation results show that this algorithm takes advantage of the statistical properties of observed values, overcomes the shortcomings of the traditional extended Kalman filter, and realizes better tracking performance.