上海交通大学学报

上海交通大学学报（自然版）

• 无线电电子学、电信技术 • 上一篇    下一篇

基于双卡尔曼滤波及贝叶斯估计的微弱GPS信号跟踪方法

周广宇，茅旭初，林庆恩，曹意
  

  1. (上海交通大学 仪器科学与工程系， 上海 200240)
  • 收稿日期:2009-09-28 修回日期:1900-01-01 出版日期:2010-09-28 发布日期:2010-09-28

A Tracking Method for Weak GPS Signals Using Dual Kalman Filters and Bayesian Estimation

ZHOU Guangyu，MAO Xuchu，LIN Qingen，CAO Yi
  

  1. (Department of Instrument Science and Engineering, Shanghai Jiaotong University, Shanghai 200240, China)
  • Received:2009-09-28 Revised:1900-01-01 Online:2010-09-28 Published:2010-09-28

摘要： 提出了一种基于卡尔曼滤波的平方根算法以及贝叶斯估计理论的微弱GPS信号跟踪方法.采用2个耦合的扩展卡尔曼滤波器，即双卡尔曼滤波器来完成码跟踪和载波跟踪，同时，减少信号累加积分时间，以降低运算复杂度而提高收敛速度；采用基于贝叶斯估计理论的未知导航信息位处理方法，以降低在信号微弱的情况下未知导航位所带来的不利影响.仿真结果表明，利用该方法可以精确跟踪载噪比低至19 dBHz的微弱GPS信号.

关键词: 全球定位系统, 双卡尔曼滤波, 贝叶斯估计, 微弱信号处理, 跟踪

Abstract: A new method on GPS weak signal tracking based on dual squareroot Kalman filters and Bayesian Estimation was proposes. It uses a new model of Kalman filter to deal with code tracking and carrier tracking respectively. Bayesian estimation theory was introduced into this method to estimate the unknown navigation data, so that the bad effect brought by reverse of data bits is deeply alleviated. The simulation results show that the weak signal with carriertonoise ratio (C/No) as low as 19 dBHz can be well tracked by the proposed method.

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