Wavelet and power spectrum analysis of global navigation satellite system multipath error modeling and mitigation

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SummaryThis study investigates the multipath error modeling and mitigation for triple‐frequency global navigation satellite system (GNSS) signals inside South Korea. Multifrequency global positioning system (GPS), globalnaya navigatsionnaya sputnikovaya sistema (GLONASS), and Galileo data are collected in an environment where the receiver must track these three constellations in both low and high multipath scenarios. First, an advanced power spectrum analysis technique known as Welch method is performed using experimental data, and its benefits and drawbacks are described. In the second attempt, the spectrogram method is utilized to perform multipath feature time–frequency analysis. Although the abnormal frequency peak presented by the spectrogram is stable, the spectrogram does not support the precise recognition of the multipath error peak occurrence. Hence, in the third attempt, continuous wavelet transforms (CWT) are applied to highlight this type of peak resolution. The CWT function successfully indicated the maximum and minimum peak resolutions and exhibited a clear wavelet energy spread. In the final stage, experimental data are reconstructed by inverse CWT (ICWT), and comparative results in terms of root mean square before and after the ICWT are estimated. After implementing the inverse wavelet method in high and low multipath error of experimental data, overall average percentages of multipath mitigation reduction compared to actual multipath error are estimated to be 95.74% and 98.79%, respectively. This study demonstrates the high efficiency of the wavelet method as well as the effectiveness as a multipath error reduction approach. These improvements can be considered as significant in achieving high‐precision positioning accuracy.