Airborne Dual-Band Microwave Radar System for Snow Thickness Measurement

Taylor, Drew; Yan, Shiqiang; O’Neill, Charles; Gogineni, Prasad; Gürbüz, Sevgi Zübeyde; Aslan, Barbaros; Larson, Jordan; Elluru, Deepak; Kolpuke, Shriniwas; Li, Linfeng; Mahjabeen, Farin; Nunn, J.; Rahman, M. Mahbubar; Reyhani, Omid; Simpson, Christopher D.; Thomas, Ryan W.; Wattal, Shashank; Blake, Jonathan S.; Boyle, Carter; Glidden, John; Higgs, MacKenzie

doi:10.1109/igarss39084.2020.9323958

Cited by 3 publications

(2 citation statements)

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“…Nadir ultra-wideband FM-CW radar (2-18 GHz) has been flown from an aircraft platform with success in the polar regions as part of NASA Operation IceBridge, mapping snow depth on sea ice and stratigraphy in firn on the ice sheets (Panzer et al, 2013;Arnold et al, 2019). More recently, airborne FM-CW experiments have been done over seasonal snow in the mountains (Yan et al, 2017), with additional efforts being carried out at the University of Alabama in developing airborne tomography mountain applications (Taylor et al, 2020).…”

Section: Ultra-wideband Radarmentioning

confidence: 99%

Review article: Global monitoring of snow water equivalent using high-frequency radar remote sensing

et al. 2022

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Abstract. Seasonal snow cover is the largest single component of the cryosphere in areal extent, covering an average of 46 × 106 km2 of Earth's surface (31 % of the land area) each year, and is thus an important expression and driver of the Earth's climate. In recent years, Northern Hemisphere spring snow cover has been declining at about the same rate (∼ −13 % per decade) as Arctic summer sea ice. More than one-sixth of the world's population relies on seasonal snowpack and glaciers for a water supply that is likely to decrease this century. Snow is also a critical component of Earth's cold regions' ecosystems, in which wildlife, vegetation, and snow are strongly interconnected. Snow water equivalent (SWE) describes the quantity of water stored as snow on the land surface and is of fundamental importance to water, energy, and geochemical cycles. Quality global SWE estimates are lacking. Given the vast seasonal extent combined with the spatially variable nature of snow distribution at regional and local scales, surface observations are not able to provide sufficient SWE information. Satellite observations presently cannot provide SWE information at the spatial and temporal resolutions required to address science and high-socio-economic-value applications such as water resource management and streamflow forecasting. In this paper, we review the potential contribution of X- and Ku-band synthetic aperture radar (SAR) for global monitoring of SWE. SAR can image the surface during both day and night regardless of cloud cover, allowing high-frequency revisit at high spatial resolution as demonstrated by missions such as Sentinel-1. The physical basis for estimating SWE from X- and Ku-band radar measurements at local scales is volume scattering by millimeter-scale snow grains. Inference of global snow properties from SAR requires an interdisciplinary approach based on field observations of snow microstructure, physical snow modeling, electromagnetic theory, and retrieval strategies over a range of scales. New field measurement capabilities have enabled significant advances in understanding snow microstructure such as grain size, density, and layering. We describe radar interactions with snow-covered landscapes, the small but rapidly growing number of field datasets used to evaluate retrieval algorithms, the characterization of snowpack properties using radar measurements, and the refinement of retrieval algorithms via synergy with other microwave remote sensing approaches. This review serves to inform the broader snow research, monitoring, and application communities on progress made in recent decades and sets the stage for a new era in SWE remote sensing from SAR measurements.

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Section: Ultra-wideband Radarmentioning

confidence: 99%

Review article: Global monitoring of snow water equivalent using high-frequency radar remote sensing

et al. 2022

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“…Motivation. At present, to solve the problems of terrain mapping, air and space reconnaissance, and missile weapons control, Radar Systems (RS) based on aerospace vehicles are actively used [1,2]. An important feature of such advanced systems is the use of underwing, under-fuselage and other types of Antenna Arrays (AA), as well as appropriate space-time signal processing [3,4].…”

Section: Introductionmentioning

confidence: 99%

Practical imaging algorithms in ultra-wideband radar systems using active aperture synthesis and stochastic probing signals

Zhyla¹,

Volosyuk²,

Павликов³

et al. 2023

reks

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The subject of the manuscript is the algorithms for radar imaging. This research develops imaging methods and algorithms for wideband and ultrawideband active aperture synthesis systems with antenna arrays and stochastic probing signals. The use of antenna arrays makes it possible to obtain radar images without the need to move radar or antenna system in space. The use of wideband and ultra-wideband stochastic probing signals is justified by their narrow autocorrelation functions. This increased the resolution of the obtained images. The main idea of the proposed algorithms is to filter the original wideband signal into several narrowband processes. Furthermore, only the central frequencies of each narrowband signal were processed. This approach allows us to use the classical widespread methods of aperture synthesis for the case of a wideband signal. Usually, they are applicable only for narrowband signals that satisfy the condition of a quasi-monochromatic approximation. This significantly reduces the overall computational complexity of the imaging algorithm, which simplifies its further practical implementation on the existing radioelement base. Because of the simulation, a primary radar image has been obtained and the overall performance of the proposed approach to processing wideband signals has been confirmed. An increase in the quality of the obtained image when using a multiple of frequency ranges is shown. An experimental study of the effect of processing a wideband signal only at its centre frequency instead of the entire frequency band is conducted. During the experiment, the correlation functions of the signals received by two spaced receivers were obtained. As a result, the Van Cittert-Zernike theorem has been experimentally confirmed. It allows signal processing only at its centre frequency instead of the entire frequency band. Simultaneously, the prospect of expanding the bandwidth of the probing signal is indicated. It, in the presence of a wideband element base and devices for high-speed signal processing, will further increase the imaging resolution of a radar system.

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Review Article: Global Monitoring of Snow Water Equivalent using High Frequency Radar Remote Sensing

Tsang

Durand

Derksen

et al. 2021

Preprint

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Abstract. Seasonal snow cover is the largest single component of the cryosphere in areal extent, covering an average of 46 million square km of Earth's surface (31 % of the land area) each year, and is thus an important expression of and driver of the Earth’s climate. In recent years, Northern Hemisphere spring snow cover has been declining at about the same rate (~ −13 %/decade) as Arctic summer sea ice. More than one-sixth of the world’s population relies on seasonal snowpack and glaciers for a water supply that is likely to decrease this century. Snow is also a critical component of Earth’s cold regions' ecosystems, in which wildlife, vegetation, and snow are strongly interconnected. Snow water equivalent (SWE) describes the quantity of snow stored on the land surface and is of fundamental importance to water, energy, and geochemical cycles. Quality global SWE estimates are lacking. Given the vast seasonal extent combined with the spatially variable nature of snow distribution at regional and local scales, surface observations will not be able to provide sufficient SWE information. Satellite observations presently cannot provide SWE information at the spatial and temporal resolutions required to address science and high socio-economic value applications such as water resource management and streamflow forecasting. In this paper, we review the potential contribution of X- and Ku-Band Synthetic Aperture Radar (SAR) for global monitoring of SWE. We describe radar interactions with snow-covered landscapes, characterization of snowpack properties using radar measurements, and refinement of retrieval algorithms via synergy with other microwave remote sensing approaches. SAR can image the surface during both day and night regardless of cloud cover, allowing high-frequency revisit at high spatial resolution as demonstrated by missions such as Sentinel-1. The physical basis for estimating SWE from X- and Ku-band radar measurements at local scales is volume scattering by millimetre-scale snow grains. Inference of global snow properties from SAR requires an interdisciplinary approach based on field observations of snow microstructure, physical snow modelling, electromagnetic theory, and retrieval strategies over a range of scales. New field measurement capabilities have enabled significant advances in understanding snow microstructure such as grain size, densities, and layering. We describe radar interactions with snow-covered landscapes, the characterization of snowpack properties using radar measurements, and the refinement of retrieval algorithms via synergy with other microwave remote sensing approaches. This review serves to inform the broader snow research, monitoring, and applications communities on progress made in recent decades, and sets the stage for a new era in SWE remote-sensing from SAR measurements.

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Airborne Dual-Band Microwave Radar System for Snow Thickness Measurement

Cited by 3 publications

References 5 publications

Review article: Global monitoring of snow water equivalent using high-frequency radar remote sensing

Review article: Global monitoring of snow water equivalent using high-frequency radar remote sensing

Practical imaging algorithms in ultra-wideband radar systems using active aperture synthesis and stochastic probing signals

Review Article: Global Monitoring of Snow Water Equivalent using High Frequency Radar Remote Sensing

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