# Real-Time Water Level Monitoring Based on GNSS Dual-Antenna Attitude Measurement
## 5 Discussion  
In this study, we propose a novel real-time water level monitoring method based on GNSS dual-antenna attitude measurement. Our experimental results demonstrate that our method can achieve real-time water level monitoring for extended periods of time under calm water conditions and can achieve monitoring accuracy at the centimeter level. We discovered that errors in monitoring results also increased when water levels changed more significantly. We believe this is partly due to a lack of synchronization between the timing of water gauge data and GNSS-R data collection. Water gauge data records water surface height at a specific moment, while GNSS-R data represents the average water surface height over a ten-minute period. As a result, when water levels change more significantly, the discrepancy between GNSS-R data and water gauge data increases. Additionally, multi-path effects may also contribute to this phenomenon. When the amplitude of water surface dynamics is significant, wave motion on the water surface causes multiple reflections of GNSS signals, leading to increased multi-path error and decreased measurement precision. The multipath error is a significant source of error in carrier phase attitude measurement, with a theoretical maximum of one-fourth of the carrier wavelength [46]. In water level measurement using an LHCP antenna to receive reflected signals from the water surface, multipath effects are the primary cause of measurement inaccuracy. When electromagnetic signals reflect off the surface of the water, they interact with the waves and irregular shapes of the water's surface. As a result, the signals undergo various phenomena, including reflection, refraction, and diffraction, during propagation. These phenomena can cause the signals to travel through multiple paths, which leads to the generation of multipath effects. To achieve millimeter-level accuracy, errors caused by multipath effects must be reduced. Due to the complexity of multipath forms, we plan to introduce a simplified model in future work to simulate the impact of multipath effects on baseline vector solutions through the simulation of actual environmental tests. As shown in Figure 10, the trends in GNSS-R altimetry data and water scale data from 4 July to 8 August 2022 are generally consistent and accurately reflect changes in water levels. However, between 10 July and 14 July, GNSS-R altimetry results were unable to respond in a timely manner to slight changes in water levels. To determine the cause of this phenomenon, we first examined the raw data from GNSS-R altimetry results. As shown in Figure 14, the number of satellites tracked during this time period was mostly between 30 and 40, indicating that the equipment was functioning properly. Upon further  
Figure 13: Corrected water level changes for the period 4 July to 8 August 2022.  
examination of our algorithm, we discovered issues with baseline processing. Small changes in baseline length, within the range of 1 cm-3 cm, were mistakenly identified as errors and ignored. As a result, the baseline length remained constant from one epoch to another. In future work, we plan to remove this logic to achieve higher accuracy in water level monitoring. The experimental design of this study has some limitations that warrant further investigation. Firstly, the feasibility of our proposed method was only tested in a single scenario. In future studies, we aim to conduct comparative experiments to examine the impact of various factors such as water depth, distance from the antenna to the water surface, rainfall, satellite elevation angle, and water surface roughness on water level measurement accuracy. This will enable us to establish the robustness and generalizability of our method. Secondly, the receiver we developed was limited by time and financial constraints, which restricted our ability to record data received by both RHCP and LHCP antennas. Consequently, we were unable to perform a post hoc analysis of the data collected.