스마트폰 GNSS 위치 정확도 향상을 위한 C/N0와 코드의사거리 잔차 기반 가중값 모델 개발
Development of a Weighting Model Based on C/N0 and Code Pseudorange Residuals for Smartphone GNSS Positioning
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초록
With the availability of smartphone GNSS raw measurement data, research on enhancing positioning accuracy using smartphones has become increasingly prominent. Despite the widespread use of C/N0-based weighting models to mitigate multipath errors, these models do not sufficiently account for the intrinsic characteristics of the observations, resulting in unstable positioning accuracy. To address this limitation, this study proposes a novel weighting model that incorporates the inherent characteristics of GNSS observations by combining code pseudorange residuals and C/N0. The proposed model utilizes a sliding window technique to calculate residuals through curve fitting of code pseudorange observations. These residuals are then combined with C/N0 to better reflect the unique features of the observations. Experimental results from tests conducted at Inha University demonstrate significant improvements in positioning accuracy. The proposed model achieved 40%, 32%, and 33% improvements in horizontal positioning accuracy and 32%, 20%, and 23% improvements in vertical accuracy for DOY 022, DOY 058, and DOY 253, respectively, compared to conventional elevation-based and C/N0-based models. These findings confirm that the proposed approach effectively improves both the accuracy and precision in smartphone GNSS positioning by addressing both observation noise and signal quality.
Abstract
With the availability of smartphone GNSS raw measurement data, research on enhancing positioning accuracy using smartphones has become increasingly prominent. Despite the widespread use of C/N0-based weighting models to mitigate multipath errors, these models do not sufficiently account for the intrinsic characteristics of the observations, resulting in unstable positioning accuracy. To address this limitation, this study proposes a novel weighting model that incorporates the inherent characteristics of GNSS observations by combining code pseudorange residuals and C/N0. The proposed model utilizes a sliding window technique to calculate residuals through curve fitting of code pseudorange observations. These residuals are then combined with C/N0 to better reflect the unique features of the observations. Experimental results from tests conducted at Inha University demonstrate significant improvements in positioning accuracy. The proposed model achieved 40%, 32%, and 33% improvements in horizontal positioning accuracy and 32%, 20%, and 23% improvements in vertical accuracy for DOY 022, DOY 058, and DOY 253, respectively, compared to conventional elevation-based and C/N0-based models. These findings confirm that the proposed approach effectively improves both the accuracy and precision in smartphone GNSS positioning by addressing both observation noise and signal quality.