Water level monitoring is critical for flood management, water resource allocation, and ecological assessment, yet traditional methods remain costly and limited in coverage. This work explores radar-based sensing as a low-cost alternative for water level estimation, leveraging its non-contact nature and robustness to environmental conditions. Commercial radar sensors are evaluated in real-world field tests, applying statistical filtering techniques to improve accuracy. Results show that a single radar sensor can achieve centimeter-scale precision with minimal calibration, making it a practical solution for autonomous water monitoring using drones and robotic platforms.

翻译：水位监测对于洪水管理、水资源分配和生态评估至关重要，但传统方法成本高昂且覆盖范围有限。本研究探索基于雷达的传感技术作为水位估算的低成本替代方案，利用其非接触特性和对环境条件的鲁棒性。通过实地测试评估商用雷达传感器，并应用统计滤波技术以提高精度。结果表明，单个雷达传感器在最小化校准的情况下可实现厘米级精度，为基于无人机和机器人平台的自主水位监测提供了实用解决方案。