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This chapter establishes a comprehensive methodological framework for cycle slip detection and repair. Commencing with multi-frequency signal processing architecture, the chapter develops a geometry-based ionosphere-weighted estimator that innovatively integrates single-differenced ionospheric biases for effective cycle slip and data gap repair, validated by extensive experiments. Progressing to single-frequency scenarios, the analysis introduces a dual-domain detection paradigm combining positional polynomial fitting in coordinate domain with partial cycle slip resolution in ambiguity domain. The results demonstrate significant improvements in accuracy and reliability, ensuring continuous high-precision positioning across various conditions.

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Cycle Slip Detection and Repair

  • 章节

  • 出版模式：

    开放获取

  • 发表日期：

    2025年

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  • Bofeng Li,
  • Zhetao Zhang,
  • Weikai Miao

摘要

This chapter establishes a comprehensive methodological framework for cycle slip detection and repair. Commencing with multi-frequency signal processing architecture, the chapter develops a geometry-based ionosphere-weighted estimator that innovatively integrates single-differenced ionospheric biases for effective cycle slip and data gap repair, validated by extensive experiments. Progressing to single-frequency scenarios, the analysis introduces a dual-domain detection paradigm combining positional polynomial fitting in coordinate domain with partial cycle slip resolution in ambiguity domain. The results demonstrate significant improvements in accuracy and reliability, ensuring continuous high-precision positioning across various conditions.