肖青怀,陈秉柱,谷守周,秘金钟,常军

• 1:中国测绘科学研究院
• 2:山东科技大学
• 3:自然资源部第一大地测量队

摘要(Abstract)：

针对传统伪距差分服务端压力大,以及在复杂环境下进行导航定位,某些历元卫星信号弱、卫星数不足、无法连续定位的问题,该文提出了基于扩展卡尔曼滤波算法的虚拟格网伪距差分方法。该方法充分利用先验信息和动力学模型,解决了复杂环境中动态定位结果不连续、定位精度低等问题。为验证算法的有效性,该文分别进行了动态、静态实验,并与最小二乘结果进行对比,实验结果表明:静态模式下,卡尔曼滤波算法比最小二乘算法的定位精度,在N、E、U方向分别提高48.3%、47.1%、52.5%;动态模式下,卡尔曼滤波算法比最小二乘算法更加稳定,更适合复杂环境定位。

关键词(KeyWords)： 卡尔曼滤波;虚拟格网;伪距差分;最小二乘

Abstract:

Keywords:

基金项目(Foundation): 国家重点研发计划课题项目（2016YFB0501801,2016YFB0502105,2016YFB0502101）;; 全球连续监测评估系统项目（CFZX0301040308-06）;; 中国测绘科学研究院基本科研业务费项目（AR1901）;; 湖南省自然资源调查与监测工程技术研究中心开放课题（2020-10）

作者(Author): 肖青怀,陈秉柱,谷守周,秘金钟,常军

DOI: 10.16251/j.cnki.1009-2307.2021.02.011

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