A Mirror-Reflection Method for Measuring Microwave Emissivity of Flat Scenes with Ground-Based Radiometers
Accurate brightness temperature (TB) measurements and microwave emissivity retrieval in passive microwave sensing conventionally rely on absolute radiometric calibration, which often requires additional hardware and complex procedures. Under well-defined geometric and environmental conditions, this study proposes a mirror-reflection-based method for measuring the microwave emissivity of flat scenes using ground-based radiometers without conventional absolute calibration. The method employs a simplified four-step observation sequence, in which the radiometer measures the pure flat scene, the flat scene with mirror reflection, the reference wall, and the cold sky. A geometric model is developed to determine the effective incidence-angle range, and an analytical framework is developed to evaluate retrieval accuracy. Numerical simulations are conducted to examine the effects of scene material, reference-wall property, operating frequency, polarization, and radiometric sensitivity. Outdoor experiments are further performed to assess feasibility under practical measurement conditions. The results show that, within moderate incidence-angle ranges and under stable radiometric conditions, the retrieved emissivities of flat scenes agree well with theoretical predictions. These findings indicate that the proposed mirror-reflection-based approach provides a feasible supplementary or alternative solution for emissivity estimation of flat targets in ground-based measurements when absolute calibration is unavailable or impractical, rather than a replacement for conventional calibration techniques.
Authors
- Xiaokang Mei (ORCID: https://orcid.org/0000-0002-3764-8148)
- Yiming Xu (ORCID: https://orcid.org/0000-0003-4001-9307)
- J.P. Chen
- Hailiang Lu
- Shilin Li
- Yun Cheng
- Taoyun Zhou
Institutions
- Hunan University of Humanities, Science and Technology (CN)
- Wuhan University (CN)
Publication Details
- Journal
- Remote Sensing
- Published
- 2026-01-20
- DOI
- https://doi.org/10.3390/rs18020341
- Primary Topic
- Soil Moisture and Remote Sensing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China