Multi-Frequency GNSS-IR Water-Level Estimation Using NMEA Observations from Low-Cost GNSS Receivers

The high-precision, continuous monitoring of the surface water level is of great importance for water resource management and the conservation of ecological systems. This study proposes a GNSS-IR-based water-level estimation method using NMEA observations collected from low-cost GNSS receivers. First, the NMEA-recorded satellite elevation angle, azimuth angle, and signal-to-noise ratio (SNR) are processed using time-series characteristics for improving the resolution and applicability of these GNSS observations. Then, the multi-frequency GNSS signal-based reflector height inversion models are developed by making use of the Lomb–Scargle periodogram method. Finally, the Velocity Pausing Particle Swarm Optimization (VPPSO) algorithm is employed to calculate the reflector height estimation and thus the water level. Two experimental data sets collected in two different environments were used to test the proposed method. The experimental results show that the root mean square error (RMSE) of the water-level estimation error is less than 6 cm for the proposed method when the in situ ones are in the range of 196.4 cm to 296.1 cm. This study provides a theoretical and technical foundation for the development of the low-cost GNSS-IR water-level measuring instrument.