基于自适应扩展卡尔曼滤波的载波跟踪算法

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基于自适应扩展卡尔曼滤波的载波跟踪算法

李理敏^1,2, 龚文斌², 刘会杰^1,2, 余金培^1,2

1. 中国科学院上海微系统与信息技术研究所, 上海 200050;
2. 中国科学院上海微小卫星工程中心, 上海 200050

收稿日期:2011-09-05 修回日期:2011-10-11 出版日期:2012-07-25 发布日期:2012-07-24
通讯作者: 龚文斌,Tel.: 021-62511070-2419 E-mail: gongwb@mail.sim.ac.cn E-mail:gongwb@mail.sim.ac.cn
基金资助:
上海市自然科学基金(11ZR1435000, 10ZR1429100);上海市产业技术创新服务平台建设(10DZ2291700)

A Carrier Tracking Algorithm Based on Adaptive Extended Kalman Filter

LI Limin^1,2, GONG Wenbin², LIU Huijie^1,2, YU Jinpei^1,2

1. Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China;
2. Shanghai Engineering Center for Microsatellites, Chinese Academy of Sciences, Shanghai 200050, China

Received:2011-09-05 Revised:2011-10-11 Online:2012-07-25 Published:2012-07-24
Supported by:
Natural Science Foundation of Shanghai City (11ZR1435000, 10ZR1429100); Industrial Technology Innovation Service Platform of Shanghai City (10DZ2291700)

摘要/Abstract

摘要： 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。

关键词: 载波相位, 扩展卡尔曼滤波, 新息, 残差, 噪声方差

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

中图分类号:

李理敏, 龚文斌, 刘会杰, 余金培. 基于自适应扩展卡尔曼滤波的载波跟踪算法[J]. 航空学报, 2012, 33(7): 1319-1328.

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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E-mail：hkxb@buaa.edu.cn

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

基于自适应扩展卡尔曼滤波的载波跟踪算法

A Carrier Tracking Algorithm Based on Adaptive Extended Kalman Filter

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