Scholarlink

<p>Currently, smartphones positioning based on Global Navigation Satellite System (GNSS) have often struggled to provide high-accuracy results due to poor data quality. However, both the widely used elevation-dependent weighting method and the Signal-to-Noise Ratio (SNR)-based weighting method have certain limitations when applied to smartphones, making it difficult to effectively down-weight poor-quality observations. Therefore, we propose a new weighting method based on precise velocity estimation. The new method utilizes the residuals of velocity estimation as a weighting indicator, in combination with the SNR-based weighting method, to develop a specific weighting strategy. Then, 168 sets of smartphone data were analyzed in the experiment. The results demonstrate that the new method shows a higher correlation between the weights and actual pseudorange observation errors, with an average correlation coefficient of -0.413, compared to -0.170 and -0.295 for elevation-dependent and SNR-based weighting methods, respectively. As for positioning accuracy, compared to the elevation-dependent weighting method, the 95% confidence level horizontal positioning error in complex environments is reduced by 6.57&#xa0;m, corresponding to an improvement by 32.46%. Similarly, compared to the SNR-based weighting method, the 95% confidence level horizontal positioning error is reduced by 5.35&#xa0;m, corresponding to an improvement by 28.12%.</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

Improving smartphone precise positioning based on a new weighting method

  • 期刊论文

  • 发表日期：

    2025年6月15日

查看全文
  • Liwenle Liu,
  • Jun Huang,
  • Xiaopeng Gong,
  • Jinming Mu,
  • Lei Xia,
  • Shengfeng Gu,
  • Yidong Lou

摘要

Currently, smartphones positioning based on Global Navigation Satellite System (GNSS) have often struggled to provide high-accuracy results due to poor data quality. However, both the widely used elevation-dependent weighting method and the Signal-to-Noise Ratio (SNR)-based weighting method have certain limitations when applied to smartphones, making it difficult to effectively down-weight poor-quality observations. Therefore, we propose a new weighting method based on precise velocity estimation. The new method utilizes the residuals of velocity estimation as a weighting indicator, in combination with the SNR-based weighting method, to develop a specific weighting strategy. Then, 168 sets of smartphone data were analyzed in the experiment. The results demonstrate that the new method shows a higher correlation between the weights and actual pseudorange observation errors, with an average correlation coefficient of -0.413, compared to -0.170 and -0.295 for elevation-dependent and SNR-based weighting methods, respectively. As for positioning accuracy, compared to the elevation-dependent weighting method, the 95% confidence level horizontal positioning error in complex environments is reduced by 6.57 m, corresponding to an improvement by 32.46%. Similarly, compared to the SNR-based weighting method, the 95% confidence level horizontal positioning error is reduced by 5.35 m, corresponding to an improvement by 28.12%.