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In this paper, based on an autoregressive (AR) model, the combination of MW and second-order time-difference phase ionosphere residual (STPIR) for cycle slip detecting and repairing under strong multipath conditions is realized (AMS). With the assistance of an AR model, AMS obtains an efficient and accurate real-time mobility detecting scheme. In addition, the combination of MW and STPIR can address the deficiencies and improve the efficiency of detection and correction, particularly under strong multipath conditions. To evaluate the feasibility and reliability of this method, a variety of cycle slip situations are tested by comparing with two traditional methods, i.e. MW and STPIR. The result shows that AMS has a higher success rate of cycle slip detection and correction compared with the traditional methods.

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An Autoregressive Model-Assisted Combination of MW and STPIR for Cycle Slip Detection and Correction Under Strong Multipath Conditions

  • 会议论文

  • 发表日期：

    2025年

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  • Zhang Hao,
  • Juan Xu,
  • Ying Han,
  • Yuyang Zhang,
  • Jiarui Zhao

摘要

In this paper, based on an autoregressive (AR) model, the combination of MW and second-order time-difference phase ionosphere residual (STPIR) for cycle slip detecting and repairing under strong multipath conditions is realized (AMS). With the assistance of an AR model, AMS obtains an efficient and accurate real-time mobility detecting scheme. In addition, the combination of MW and STPIR can address the deficiencies and improve the efficiency of detection and correction, particularly under strong multipath conditions. To evaluate the feasibility and reliability of this method, a variety of cycle slip situations are tested by comparing with two traditional methods, i.e. MW and STPIR. The result shows that AMS has a higher success rate of cycle slip detection and correction compared with the traditional methods.