Method for remote measurement of snow and ice thickness using frequency modulation for airborne monitoring systems

G.Yu. Stepanov

doi:10.18127/j20700814-202605-09

Method for remote measurement of snow and ice thickness using frequency modulation for airborne monitoring systems

research article UDC 004.93 Pages: 59-65 doi.org/10.18127/j20700814-202605-09

¹ Saint Petersburg State University of Aerospace Instrumentation (St.-Petersburg, Russia)

Keywords: Frequency-modulated continuous-wave compact airborne radar system small aerial vehicle remote sensing simulation modeling ice thickness snow thickness radargram

Abstract

At present, monitoring the thickness of snow and ice cover is essential for a wide range of applications. Traditional thickness measurement methods have significant limitations and drawbacks. Consequently, there is a growing need for the development of remote measurement techniques based on compact airborne frequency-modulated continuous-wave radar systems.

The purpose of this study is to develop and evaluate the effectiveness of a methodology for measuring snow and ice thickness in a multilayer «air – snow – ice – water» medium through simulation modeling of a compact airborne frequency-modulated continuous-wave radar mounted on a mobile small aerial platform.

The main result of this work is the development of a simulation model for subsurface scanning of a multilayer medium, which confirmed the effectiveness and feasibility of the proposed methodology for measuring snow and ice cover thickness. Accuracy assessment demonstrated that the mean absolute error is lower than or comparable to that reported in similar studies, representing an optimal result for systems of this class.

The proposed integrated model enables simultaneous measurement of snow and ice thickness and improves the efficiency of preliminary configuration and testing of compact airborne FMCW radar systems. As a result, the deployment of such systems can increase the accuracy of remote thickness measurements while eliminating the need for labor-intensive contact-based measurement methods.

Received: 13.07.2026
Approved after review: 22.07.2026
Accepted: 01.09.2026

How to cite

Степанов Г.Ю. Методика дистанционного измерения толщины снега и льда для авиационных систем бортового контроля с частотной модуляцией // Информационно-измерительные и управляющие системы. 2026. Т. 24. № 5. С. 59−65. DOI: https://doi.org/10.18127/j20700814-202605-09

References

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[1] Yan J.-B., Alvestegui D.G.-G., McDaniel J.W., Li Y., Gogineni S., Rodriguez-Morales F. Ultrawideband FMCW Radar for Airborne Measurements of Snow Over Sea Ice and Land. IEEE Transactions on Geoscience and Remote Sensing. 2017. V. 55. № 2. P. 834–843. DOI: 10.1109/TGRS.2016.2616134.

[2] Jenssen R.O.R., Eckerstorfer M., Jacobsen S. Drone-Mounted Ultrawideband Radar for Retrieval of Snowpack Properties. IEEE Transactions on Instrumentation and Measurement. 2020. V. 69. № 1. P. 221–230. DOI: 10.1109/TIM.2019.2893043.

[3] Tang A., Chahat N., Kim Y., Bharathan A., Virbila G., Marshall H.-P. A UAV Based CMOS Ku-Band Metasurface FMCW Radar System for Low-Altitude Snowpack Sensing. IEEE Journal of Microwaves. 2024. V. 4. № 1. P. 43–55. DOI: 10.1109/JMW.2023.3327188.

[4] Abushakra F., Kolpuke S., Simpson C., Reyhanigalangashi O., Pierce J., Jeong N. Snow Depth Measurements With Ultra-Wideband Compact FMCW Radar on a Small Unmanned Aircraft System. IEEE Journal of Radio Frequency Identification. 2023. V. 7. P. 343–351. DOI: 10.1109/JRFID.2023.3259240.

[5] Pomerleau P., Royer A., Langlois A., Cliche P., Courtemanche B., Madore J.-B., Picard G., Lefebvre É. Low Cost and Compact FMCW 24 GHz Radar Applications for Snowpack and Ice Thickness Measurements. Sensors. 2020. V. 20. P. 3909. DOI: 10.3390/s20143909.

[6] Kolpuke S., Simpson C.D., Abushakra F., Awasthi A.K., Reyhanigalangashi O., Pierce J. Airborne UWB FMCW Radar for Snow Depth Measurements. IEEE Transactions on Geoscience and Remote Sensing. 2022. V. 60. P. 1–15. DOI: 10.1109/TGRS.2022.3223989.

[7] Stroeve J., Nandan V., Willatt R., Tonboe R., Hendricks S., Ricker R., Mead J., Huntemann M., Itkin P., Schneebeli M., Krampe D., Spreen G., Wilkinson J., Matero I., Hoppmann M., Mallet R., Tsamados M. Surface-Based Ku- and Ka-band Polarimetric Radar for Sea Ice Studies. 2020. DOI: 10.5194/tc-2020-151.

[8] Tikhonov V.V., Boyarskii D., Sharkov E., Raev M., Repina I., Ivanov V., Alekseeva T., Komarova N. Microwave model of radiation from the multilayer “ocean-atmosphere” system for remote sensing studies of the polar regions. Progress In Electromagnetics Research B. 2014. V. 59. P. 123–133. DOI: 10.2528/PIERB14021706.

[9] Rodríguez-Morales F., Li J., Alvestefui D.G.-G., Shang J., Arnold E.J., Leuschen C.J. A Compact, Reconfigurable, Multi-UWB Radar for Snow Thickness Evaluation and Altimetry: Development and Field Trials. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2021. V. 14. P. 6755–6765. DOI: 10.1109/JSTARS.2021.3092313.

[10] Barber D.G., LeDrew E.F. Modeling synthetic aperture radar (SAR) scattering from a seasonally varying snow-covered sea ice volume at 5.3 and 9.25 GHz. Polar Research. 1994. V. 13(1). P. 35–54. DOI: 10.3402/polar.v13i1.6679.

[11] Ayhan S., Pauli S., Scherr S., Gottel B., Bhutani A., Thomas S. Millimeter-Wave Radar Sensor for Snow Height Measurements. IEEE Transactions on Geoscience and Remote Sensing. 2017. V. 55. № 2. P. 854-861. DOI: 10.1109/TGRS.2016.2616441.

[12] Maaß N., Kaleschke L., Tian-Kunze X., Drusch M. Snow thickness retrieval over thick Arctic Sea ice using SMOS satellite data // The Cryosphere. 2013. V. 7. P. 1971–1989. DOI:10.5194/tc-7-1971-2013

[13] Mills P., Georg H. Sea Ice Brightness Temperature as a Function of Ice Thickness: Computed curves for AMSR-E and SMOS (frequencies from 1.4 to 89 GHz). arXiv (Cornell University). Cornell University. 2012. DOI:10.48550/arXiv.1202.3802.

[14] Kolpuke S., Abushakra F., Gogineni S.P., Braaten D., Taylor D., Larson J.D. Airborne Multichannel UWB FMCW Radar for Snow Depth Measurements. IEEE Transactions on Geoscience and Remote Sensing. 2024. V. 62. P. 1–18. DOI: 10.1109/TGRS.2024.3359125.

Abstract

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