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A SINS-aided two-step fast acquisition method for GNSS signal based on compressive sensing

机译:基于压缩感知的捷联惯导辅助两步快速获取GNSS信号的方法

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摘要

The Global navigation satellite system(GNSS)multi-mode compatible andmulti-frequency informationnot only improves information redundancy but also eliminates errors such as ionosphericdelays to improve positioning performance. However, multi-mode and multi-frequency observationinformation increases the hardware overhead and computational complexity, especiallythe signal acquisition. In this contribution, according to the strong complementarity betweenGNSS and Strapdown inertial navigation system (SINS) and the sparsity of the GNSS signalspreading code in the autocorrelation domain, a SINS-aided fast acquisition method for GNSSsignals based on Compressive sensing (CS) is proposed. First, the inertia information of SINS narrowsthe Doppler frequency search range; then, the CS is applied to measure compressively theGNSS signal in two steps, ie, the first step is to narrow down the code phase search range, andthe second step is to determine the code phase of the half chip accuracy. Finally, the proposedmethod and the other two typical acquisition methods are compared by the detection probabilityand the Mean acquisition time (MAT). Theoretical analysis and experimental results showthat the proposed method can not only reduce the number of correlators and computationalcomplexity but also improve the detection probability and reduce the MAT.
机译:全球导航卫星系统(GNSS)的多模式兼容和多频信息不仅提高了信息冗余度,而且消除了电离层延迟等误差,从而提高了定位性能。但是,多模式和多频率的观测信息会增加硬件开销和计算复杂度,尤其是信号采集。在此贡献中,针对GNSS与捷联惯性导航系统(SINS)之间的强互补性以及自相关域中GNSS信号扩展代码的稀疏性,提出了一种基于压缩感知(CS)的SINS辅助GNSS信号快速获取方法。首先,SINS的惯性信息使多普勒频率搜索范围变窄。然后,将CS分两步进行压缩GNSS信号的测量,第一步是缩小码相位搜索范围,第二步是确定半码片精度的码相位。最后,通过检测概率和平均获取时间(MAT),比较了所提出的方法和其他两种典型的获取方法。理论分析和实验结果表明,该方法不仅可以减少相关器的数量和计算复杂度,而且可以提高检测概率,降低MAT。

著录项

  • 来源
    《Concurrency, practice and experience》 |2019年第24期|e5369.1-e5369.10|共10页
  • 作者

    Junbing Cheng; Dengao Li;

  • 作者单位

    College of Information and Computer Taiyuan University of Technology Taiyuan China;

    College of Information and Computer Taiyuan University of Technology Taiyuan China Shanxi Engineering Technology Research Center for Spatial Information Network Taiyuan University of Technology Taiyuan China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    compressive sensing; signal acquisition; SINS; SNR;

    机译:压缩感测信号采集罪恶;信噪比;

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