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

用于提高全球定位系统定位估计速度的滤波算法

武静，茅旭初   

  1. （上海交通大学 电子信息与电气工程学院， 上海 200240）
  • 收稿日期:2007-10-24 修回日期:1900-01-01 出版日期:2008-10-28 发布日期:2008-10-28
  • 通讯作者: 茅旭初

A Filter Algorithm for Improving the Calculation Speed of
GPS Positioning Estimation

WU Jing, MAO Xu-chu   

  1. (School of Electronic, Information and Electrical Engineering,
    Shanghai Jiaotong University, Shanghai 200240, China)
  • Received:2007-10-24 Revised:1900-01-01 Online:2008-10-28 Published:2008-10-28
  • Contact: MAO Xu-chu

摘要： 为了提高全球定位系统（GPS）高精度定位的解算速度，从原理上比较了平淡卡尔曼滤波（UKF）及其改进算法和超球面平淡卡尔曼滤波（SUKF）及其改进型等非线性滤波估计算法，提出了将SUKF的改进型算法应用于单机GPS的定位估计.实验表明：该算法能够在保证高精度定位估计的前提下提高运算速度，有效解决GPS软件接收机中高精度定位输出的实时性问题.

关键词: 全球定位系统, 平淡卡尔曼滤波, 超球面平淡卡尔曼滤波, 运算量

Abstract: To improve the calculation speed of high accuracy positioning estimation of global positioning system（GPS）, four nonlinear filtering algorithms were described and compared in theory, which are unscented Kalman filter (UKF) and its modified algorithm, spherical unscented Kalman filter (SUKF) and its modified version. Then the modified SUKF was proposed as an optimal estimation algorithm in the standalone GPS positioning. The experimental results show that the modified SUKF achieves high positioning accuracy and improves the calculation speed significantly; it can effectively solve the realtime problem with high positioning accuracy in GPS software receiver.

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