Scholarlink

<p>In satellite-based navigation systems, multipath is the most significant source of error. Multipath disturbance occurs when satellite signals reflect off nearby objects, such as trees, buildings, and vehicles, causing the signals to arrive through multiple paths. Multipath error contains low- and medium-frequency components, which can lead to biased position estimates. The non-stationary nature of the global navigation satellite system (GNSS) code multipath error motivated us to explore tools that can help investigate its transient nature. This paper aims to investigate the efficacy of time-frequency methods in detecting and analyzing the frequency content of GNSS multipath error, as well as for its denoising. The proposed method is based on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) in conjunction with the detrended fluctuation analysis (DFA). Multipath estimation is performed using the code-minus-carrier (CMC) technique and pseudorange multipath observables. Real-world datasets were analyzed, wherein the CMC time series is decomposed, its time-frequency signature identified, and code multipath error terms extracted. Experimental results demonstrate that the proposed ICEEMDAN-DFA method effectively analyzes and mitigates GNSS code multipath error.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

GNSS Multipath Error Analysis Based on Improved CEEMDAN and Detrended Fluctuation Analysis

  • 期刊论文

  • 发表日期：

    2025年2月9日

查看全文
  • Naraiah RP,
  • Naveen Kumar P,
  • Abhijit Dey

摘要

In satellite-based navigation systems, multipath is the most significant source of error. Multipath disturbance occurs when satellite signals reflect off nearby objects, such as trees, buildings, and vehicles, causing the signals to arrive through multiple paths. Multipath error contains low- and medium-frequency components, which can lead to biased position estimates. The non-stationary nature of the global navigation satellite system (GNSS) code multipath error motivated us to explore tools that can help investigate its transient nature. This paper aims to investigate the efficacy of time-frequency methods in detecting and analyzing the frequency content of GNSS multipath error, as well as for its denoising. The proposed method is based on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) in conjunction with the detrended fluctuation analysis (DFA). Multipath estimation is performed using the code-minus-carrier (CMC) technique and pseudorange multipath observables. Real-world datasets were analyzed, wherein the CMC time series is decomposed, its time-frequency signature identified, and code multipath error terms extracted. Experimental results demonstrate that the proposed ICEEMDAN-DFA method effectively analyzes and mitigates GNSS code multipath error.