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<p>In urban environments, degraded observation conditions of Global Navigation Satellite System (GNSS) frequently lead to failure in Ambiguity Resolution (AR), significantly compromising attitude determination accuracy. To address this challenge, this study proposes the Pitch-constrained LAMBDA (PC-LAMBDA) method, which leverages pitch angle information to effectively enhance AR success rates for the GNSS compass. The pitch angle can be derived either from the flatness characteristics of urban roads or calculated using accelerometer outputs, both approaches being feasible for vehicle-mounted GNSS attitude determination platforms without requiring high hardware specifications. Furthermore, when constructing the boundary functions of the ambiguity objective function to accelerate the AR process, a novel bounding function group approach is proposed that combines multiple upper and lower bounding functions, making the boundary functions easily designed and more approximate to the complex objective function. Experimental results from two vehicular tests conducted in complex urban environments demonstrate that the proposed method effectively improves AR success rates by utilizing road flatness information, particularly under conditions of limited visible satellites, where performance enhancements are more significant.</p>

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Research on the ambiguity resolution method for the GNSS compass with pitch angle constraint

  • 期刊论文

  • 发表日期：

    2026年2月12日

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  • Ming Gao,
  • Ying Xu,
  • Genyou Liu,
  • Shengliang Wang,
  • Gongwei Xiao,
  • Wenhao Zhao,
  • Zhibo Fang,
  • Xialan Chen

摘要

In urban environments, degraded observation conditions of Global Navigation Satellite System (GNSS) frequently lead to failure in Ambiguity Resolution (AR), significantly compromising attitude determination accuracy. To address this challenge, this study proposes the Pitch-constrained LAMBDA (PC-LAMBDA) method, which leverages pitch angle information to effectively enhance AR success rates for the GNSS compass. The pitch angle can be derived either from the flatness characteristics of urban roads or calculated using accelerometer outputs, both approaches being feasible for vehicle-mounted GNSS attitude determination platforms without requiring high hardware specifications. Furthermore, when constructing the boundary functions of the ambiguity objective function to accelerate the AR process, a novel bounding function group approach is proposed that combines multiple upper and lower bounding functions, making the boundary functions easily designed and more approximate to the complex objective function. Experimental results from two vehicular tests conducted in complex urban environments demonstrate that the proposed method effectively improves AR success rates by utilizing road flatness information, particularly under conditions of limited visible satellites, where performance enhancements are more significant.