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Computer Engineering ›› 2010, Vol. 36 ›› Issue (16): 286-287. doi: 10.3969/j.issn.1000-3428.2010.16.102

• Networks and Communications • Previous Articles     Next Articles

Data Processing Algorithm Based on Adaptive Kalman Filtering for Common View System

ZHAO Dang-li, ZHAI Hui-sheng, HU Yong-hui   

  1. (National Time Service Center, Chinese Academy of Sciences, Lintong 710600)
  • Online:2010-08-20 Published:2010-08-17

基于自适应Kalman滤波的共视数据处理算法

赵当丽,翟慧生,胡永辉   

  1. (中国科学院国家授时中心,临潼 710600)
  • 作者简介:赵当丽(1975-),女,硕士,主研方向:GPS,北斗卫星共视系统;翟慧生、胡永辉,研究员
  • 基金资助:

    国家电网电力科学研究院基金资助项目(0719KF1623)

Abstract:

The time difference between the local 1PPS time reference and the satellite one including outliers is important effect on instability of the satellite 1PPS signal and ambient interference and measurement noise in GPS/BD “dual-mode” satellite common view system. An adaptive Kalman filtering based on residual chi-square test is presented, which is effectively resistant to outliers and increases the result of common view comparison.

Key words: “dual-mode&rdquo, satellite common view system, adaptive Kalman filtering, outlier, residual chi-square test

摘要:

在GPS、北斗“双模”卫星共视系统中,由于卫星秒的不稳定性、环境干扰及测量噪声等不确定因素的存在,使得卫星秒与本地钟秒的时差数据出现较大的跳变,直接影响最后的卫星共视比对结果。为此,提出一种基于残差(χ2)检验法的自适应卡尔曼滤波算法,有效地剔除野值,使时差数据更接近真实钟差,提高了卫星共视系统的比对精度。

关键词: “双模”卫星共视系统, 自适应卡尔曼滤波, 野值, 残差(χ2)检验法

CLC Number: