基于自适应扩展卡尔曼滤波的载波跟踪算法

Abstract

Abstract: 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.

Key words: carrier phase, extended Kalman filter, innovation, residual, noise covariance

CLC Number:

LI Limin, GONG Wenbin, LIU Huijie, YU Jinpei. A Carrier Tracking Algorithm Based on Adaptive Extended Kalman Filter[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2012, 33(7): 1319-1328.

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A Carrier Tracking Algorithm Based on Adaptive Extended Kalman Filter

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