基于自适应扩展卡尔曼滤波的载波跟踪算法

精确的载波相位测量是精密测距中一个很重要的研究点。针对传统扩展卡尔曼滤波(EKF)的固定设计在先验信息不充分和动态变化环境中存在的不足,提出了一种基于自适应扩展卡尔曼滤波(AEKF)的载波跟踪算法。该算法通过实时监测滤波器新息或残差的动态变化,以修正状态噪声方差和观测噪声方差,进而调整滤波器增益,控制状态预测值和观测值在滤波结果中的权重。理论分析和仿真结果表明,本算法充分利用了观测信号的统计特性,克服了传统扩展卡尔曼滤波算法的不足,能够获得更好的载波跟踪性能。

A Carrier Tracking Algorithm Based on Adaptive Extended Kalman Filter

Accurate carrier phase measurement is an important research focus in precise ranging.Because the traditional extended Kalman filter(EKF) has some limitations in dynamic environments with insufficient priori information,this paper proposes a carrier tracking algorithm based on adaptive extended Kalman filter(AEKF).This algorithm monitors the changes in innovations or residuals to correct the process and measurement noise covariances,and then adjusts the filter gain to control the weights 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 carrier tracking performance.