Android smartphone-based GNSS multipath reflectometry for estimating the reflector height

With the rapid popularization of mobile smart devices, developing applications of GNSS-MR techniques using low-cost GNSS antennas has become both possible and significant. Aiming to address the high hardware requirements of the classical GNSS-MR method and the susceptibility of low-cost GNSS observations to noise interference, we propose a high-precision ground-based GNSS-MR altimetry algorithm for Android smartphones. Firstly, raw signal-to-noise ratio (SNR) data from multiple GNSS is collected using two smartphones: the iQOO Neo3 and Xiaomi 8. After processing the data with a multi-scale wavelet decomposition algorithm, a nonlinear least squares method is employed to extract the oscillation frequency of the high-frequency coefficients via waveform fitting, retrieving the reflector heights (RH) between the land surface and the antenna phase center. Finally, the performance of the proposed method is validated by comparing the RHs obtained with in situ measurements and those from geodetic GNSS receivers. The results demonstrate that noise signals negatively impact altimetry using Android smartphone-based GNSS-MR. The root mean square errors (RMSEs) of GNSS-MR altimetry for both GPS and BDS satellites are less than 10 cm, and the stability is significantly better than that of other single-system estimations. Compared to geodetic GNSS receivers, smartphones benefit from longer SNR arcs. The proposed method provides a foundational theory for developing low-cost ground-based and low-altitude airborne GNSS-MR monitoring equipment.