Smartphone pseudorange multipath extraction based on variational mode decomposition and wavelet transform

• Published in: IEEE transactions on instrumentation and measurement 2023-01, Vol.72, p.1-1
• Main Authors: Liu, Qi, Gao, Chengfa, Shang, Rui, Gao, Wang, Zhang, Ruicheng
• Format: Article
• Language: English
• Subjects: Code-minus-carrier; Decomposition; Discrete wavelet transforms; Errors; Filtering; Global navigation satellite system; Global navigation satellite system (GNSS); Interference; Multipath extraction; Performance evaluation; Satellite observation; Satellites; Signal processing algorithms; Smartphone; Smartphones; Time-frequency analysis; Transforms; Urban environments; Variational mode decomposition (VMD); Wavelet analysis; Wavelet transform; Wavelet transforms
• ISSN: 0018-9456; 1557-9662
• DOI: 10.1109/TIM.2023.3290318

The development of multi-constellation and multi-frequency global navigation satellite system (GNSS) chips has improved the positioning performance of smartphones. However, the low-gain antennas equipped with smartphones make GNSS observations subject to multipath interference, which seriously affects the high-precision positioning of smartphones in urban environment. Considering the low frequency characteristics of multipath errors, we propose a pseudorange multipath extraction method based on variational mode decomposition (VMD) and wavelet transform. VMD is used to extract multipath components from code-minus-carrier (CMC) observation, and wavelet-based method is used to reduce the observation noise. Compared with methods that only use VMD or wavelet transform, the proposed method can reduce the influence of observation noise while preserving the multipath components. The root mean square (RMS) of extracted multipath by the proposed method for different smartphones is improved by about 15%-30%, and the observations of L5/E5a have stronger anti-interference. To further evaluate the performance of the proposed method, we conduct single point positioning experiments with different smartphones in different multipath environments. The results show that the proposed method can effectively extract the pseudorange smartphone multipath errors. In the weak multipath environment, the plane accuracy and elevation accuracy are improved by 20% and 16% on average, while in strong multipath environment, the positioning result after multipath processed has some improvement, but there is still room for improvement. This method can provide new ideas for smartphone multipath processing in urban environments.