Research on Snow Depth Measurement Technology Based on Dual-Band Microwave Open Resonant Cavity
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摘要: 能实时准确测量雪层厚度并进行预警的设备对于保护冬季长时间暴露在外界环境中的供电、通信、雷达等设备具有重要的应用价值。论文研究了基于微波矩形波导开口双腔体的雪层厚度测试方法，设计了对应的测量装置，给出了相关的构造、参数获取、数据反演策略。在此过程中，提出了基于单舱内嵌入金属隔板或频率选择表面(FSS)隔板的双腔双馈电双频段测试方法，通过大腔体低频大动态范围和小腔体高频高精度的策略结合参数相关处理算法，合理解决了大量程和高测试精度之间的矛盾。论文分析了自然降落覆盖在谐振腔开口处的不同雪层厚度对腔体的反射系数谐振频率和S参数的影响，并讨论了雪的密度、湿度对厚度测量精度的影响，比较了不同反演算法的效果，实现了1～30 mm的雪层厚度的分段测量，反演算法精度达到0.16 mm。测试精度优于1 mm。对应的技术和设备可直接或扩展用于以雪厚测试为代表的介质几何参数测试。Abstract:
Objective Large-scale winter snowfall poses a significant threat to the safety of outdoor infrastructure such as power and communication systems. Real-time monitoring of snow depth within the 1～30 mm range is crucial for precise early warning and snow removal scheduling. Satellites and radar are mostly used to detect snow depths over 10 cm, but they are bulky and have low resolution. Although recently developed planar resonant sensors based on the resonance method improve accuracy, their measurement range is compromised. To address the conflict between range and accuracy, a rectangular resonant cavity structure featuring a dual-cavity, dual-feed, and dual-frequency-band design based on the resonance method is proposed in this work, combined with an inversion algorithm. This approach achieves a large dynamic range of 1～30 mm while maintaining a high measurement accuracy of 1 mm. The designed measurement device is capable of meeting the monitoring requirements for snow depth across six intensity grades, from light snow to heavy snowstorms. Methods The research methodology comprises four main components. First, the phase-matching condition of the resonator formed by the open-ended waveguide and the snow is utilized to theoretically derive the analytical relationship between the resonant frequency and the snow depth, thereby validating the principle's feasibility. Subsequently, a single-cavity model with coaxial feeding is designed and simulated to verify its sensitivity to snow depths ranging from 1 to 25 mm, thus determining its effective operating frequency band. Then, to extend the measurement range, a dual-cavity, dual-feed model incorporating either a metal plate or a Frequency Selective Surface (FSS) as a separator is proposed. A segmented measurement strategy is adopted, where the large and small cavities are responsible for different thickness ranges, achieving stable performance with a precision of 1 mm across the 1～30 mm range under varying snow properties. Finally, an optimal data inversion scheme is selected and implemented to further enhance the measurement accuracy. Results and Discussions This study presents a snow depth measurement technique based on a dual-band open-ended microwave resonant cavity. The dynamic measurement range is successfully extended from 1～25 mm ( Fig. 4 ) for the single-cavity model to 1～30 mm (Fig. 9 ) for the dual-cavity model. Simulations demonstrate that the dual-cavity model maintains stable performance under variations in snow’s physical properties (Fig. 10 ～13 ). Its resonant frequency exhibits a regular low-frequency shift as snow depth increases (Fig. 9(a) ), while the attenuation remains below –10 dB (Fig. 9(b) ), achieving a precision of 1 mm. Finally, measured results show a consistent trend with simulations (Fig. 15 ). When combined with an efficient data processing scheme, the inversion error is less than 0.16 mm (Table 5 ), meeting the requirements for both large dynamic range and high measurement accuracy.Conclusions A dual-cavity, dual-feed, and dual-frequency snow depth measurement method incorporating either a metal plate or an FSS plate as a separator is proposed. The limitation of the insufficient dynamic range in single-cavity designs is overcome by the constructed dual-cavity structure. The measurement resolution is enhanced through the division of labor between the two frequency bands and the application of data inversion algorithms. Experimental results indicate that this scheme achieves segmented measurement of snow depths within the 1～30 mm range, with an inversion accuracy of 0.16 mm and a measured precision better than 1 mm. The study comprehensively discusses the impact of variations in snow density and humidity on the measurement accuracy of resonant frequency and attenuation. For subsequent research, machine learning methods are suggested to correlate test parameters with meteorological parameters, thereby further improving measurement accuracy and expanding the system's early-warning capability. -
Key words:
- Snow depth measurement /
- Microwave open resonant cavity /
- Data inversion
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表 2 金属板隔离的双腔体尺寸(mm)
A1 A2 B1 B2 D1 D2 H H1 H2 L1 L2 P1 P2 98.744 78.488 37.440 18.532 31.000 1.000 55.000 34.000 18.000 19.000 9.000 18.000 9.000 
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表 3 FSS单元尺寸(mm)
G1 G2 C1 C2 C3 C4 W1 W2 18.000 0.762 1.000 3.000 8.300 9.200 8.900 11.600 W3 C5 C6 C7 C8 C9 C10 W4 12.000 6.800 7.000 5.000 6.000 7.100 9.500 8.900
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表 4 双腔体模型的反演绝对误差(mm)
雪层数据点 金属板隔离模型 FSS隔离模型 算法1 算法2 算法3 算法1 算法2 算法3 1.0 0.00 0.00 0.00 0.00 0.00 0.00 3.7 0.07 –0.14 –0.04 0.50 0.18 0.17 9.2 0.18 0.15 0.02 –0.07 0.15 0.03 15.5 0.01 –0.06 –0.02 0.21 –0.18 –0.11 21.4 –0.40 –0.34 –0.29 0.16 –0.02 –0.05 27.8 0.07 –0.18 0.05 0.08 –0.01 –0.46 30.0 0.00 0.00 0.00 0.00 0.00 0.00
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表 5 加工模型的反演结果与绝对误差统计(mm)
雪层数据点 反演结果 绝对误差 1.0 1.00 0.00 5.5 5.35 0.15 15.3 15.43 -0.13 19.9 19.78 0.12 27.8 27.64 0.16 30.0 30.00 0.00
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