文章摘要
引用本文:高亚豪,左启耀,邹志勤,李峰,胡文涛.惯性辅助高动态RTK 模糊度浮点解求解算法研究[J].导航定位与授时,2017,(6):61-67 本文二维码信息
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惯性辅助高动态RTK 模糊度浮点解求解算法研究
The Research on Algorithm of Ambiguity Float Solution of High Dynamical RTK Based on Inertial Aiding
  
DOI:
中文关键词:  惯性辅助  RTK  整周模糊度  Kalman滤波  高动态
English Keywords:Inertial aiding  RTK  Integer ambiguity  Kalman filtering  High dynamic
基金项目:
作者单位
高亚豪 北京自动化控制设备研究所北京 100074 
左启耀 北京自动化控制设备研究所北京 100074 
邹志勤 北京自动化控制设备研究所北京 100074 
李峰 北京自动化控制设备研究所北京 100074 
胡文涛 北京自动化控制设备研究所北京 100074 
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中文摘要:
      载波相位差分(RTK)技术需要着重解决整周模糊度快速精确求解问题。针对高动态应用,提出一种利用惯性信息辅助求解RTK整周模糊度浮点解的算法,建立了基于加速度信息辅助的Kalman滤波器模型,分析了加速度误差和惯导信息延迟对滤波结果的影响,并通过仿真对算法的动态性能进行了深入研究。仿真结果表明,与未受辅助的Kalman滤波算法相比,基于惯性辅助的求解算法能够在高动态下获得较精确的整周模糊度浮点解,使后续整数解的搜索空间更小,提升了模糊度固定效率和成功率;在发生周跳、出现野值和跟踪到新卫星信号的情况下,该算法同样具有很好的模糊度浮点解求解性能;此外,惯导加速度的随机测量误差和信息延迟不会对算法的性能造成较大影响。
English Summary:
      As it is crucial to focus on solving the problem of fast and accurate resolution of integer ambiguity in carrier phase differential (RTK) technique, for the high dynamic application, a new method of RTK integer ambiguity float solution based on inertial information aiding is presented and a Kalman filter model based on acceleration aiding is established. The influence of acceleration error and INS information delay on the filter results are analyzed, and deep research on the dynamic performance of the algorithm by simulation is made. The simulation results show that the algorithm based on inertial aiding can obtain a more accurate integer ambiguity float solution under highly dynamic condition compared with the non auxiliary Kalman filtering algorithm. It makes the following search space of integer solution smaller and improves the efficiency and success rate of fixing ambiguity. In the event of the cycle slip, the outlier and tracking to the new satellite signals, the algorithm also has a better performance of the resolution of the ambiguity float solution similarly. Besides, the random measurement error and information delay of INS acceleration wont affect the performance of the algorithm greatly.
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