Millimeter Wave Measurement and Modeling of Terrain Scattering

Ulaby, F. T.

doi:10.21236/ada253525

Cited by 20 publications

(55 citation statements)

References 20 publications

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“…2). Sequential beam footprints spatially overlap the scene and are thus at least partially correlated [27]. The footprint centre at subsequent azimuthal and elevation steps (c b (θ n , ϕ n )) is then a function of the spatial sampling interval in azimuth (∆θ) and elevation (∆ϕ):…”

Section: A Theorymentioning

confidence: 99%

“…dust, fog) and precipitation, altering the radar received power from terrain and hence increase ranging uncertainties. Different surface types also exhibit unique radar backscatter characteristics under different viewing geometries [27] and this also impacts signal stability and hence ranging performance. For example, fluctuating targets such as vegetation are typically considered volume scatterers [38].…”

Section: B Avtis2 Point Cloud Uncertaintymentioning

confidence: 99%

“…Increased surface roughness may increase the uncertainty of AVTIS2 point clouds. Increased surface roughness reduces the correlation length of a surface [27] and hence may lead to greater variability in radar backscatter which impacts both the magnitude and the shape of the returned echo. This reduces the probability that the range to terrain measurement can be repeated at the same location and hence increases point cloud uncertainty.…”

Section: B Avtis2 Point Cloud Uncertaintymentioning

confidence: 99%

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94 GHz radar mapping of terrestrial snow cover

Harcourt¹,

Robertson²,

Macfarlane³

et al. 2021

Preprint

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<p>Terrestrial snow cover is a perennial feature throughout the global cryosphere, taking the form of individual snow patches during summer and becoming more spatially continuous in winter. The characteristics and conditions of these snowpacks can be altered by rapid changes in temperature and precipitation, significantly impacting local ecosystems, upland hydrology and snow avalanche risks. In Scotland, for example, monitoring the hazards associated with snowpack alterations is a central focus of the Scottish Avalanche Information Service (SAIS) and is essential to ensuring the safety of local communities, hill walkers and mountaineers. In this context, the development of new remote sensing techniques for snow monitoring will help the SAIS develop avalanche forecasts and potentially without the need to undertake arduous and dangerous fieldwork. Here, we aim to develop the utility of millimetre-wave radar at 94 GHz as a new remote sensing tool for monitoring snowpacks. We use a ground-based 94 GHz, real-aperture system called AVTIS2 which mechanically scans across a scene of interest to generate radar backscatter images and 3D Digital Elevation Models (DEMs). AVTIS2 uses a narrow beamwidth of 0.35&#176; (i.e. a spot size of 6 m per km) and has a maximum range of ~6 km, enabling kilometre-scale mapping at high angular resolution. This radar system has previously been successful in monitoring the topographic changes of volcanic lava domes, measuring the dynamics of active lava flows and quantifying 94 GHz radar backscatter from glacier ice. We aim to deploy the AVTIS2 millimetre-wave radar in the Cairngorms National Park, Scotland, in January/February 2021 and validate our measurements with a co-located Terrestrial Laser Scanner (TLS). Additionally, we will acquire in situ observations of snow properties to gain a better understanding of how 94 GHz radar signals interact with the snowpack. Overall, we will report on the following: (1) the radar backscatter characteristics from a variety of snow surface conditions at millimetre wavelengths; (2) point cloud and DEM differences between AVTIS2 and TLS measurements over snow-covered terrain; and (3) the effect of snowpack properties on radar backscatter and how this can be used to understand snow-associated hazards.</p>

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Section: A Theorymentioning

confidence: 99%

Section: B Avtis2 Point Cloud Uncertaintymentioning

confidence: 99%

Section: B Avtis2 Point Cloud Uncertaintymentioning

confidence: 99%

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94 GHz radar mapping of terrestrial snow cover

Harcourt¹,

Robertson²,

Macfarlane³

et al. 2021

Preprint

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“…Such a difference must be accounted for when evaluating the possible enhancement of the double bounce backscattering due to the inundation. We have assumed a simplified cosine model (Ulaby and Dobson, 1989), supposing that the variation of σ 0 with the incidence angle θ can be approximated by cos 2 (θ). With this hypothesis, if θ x and θ y are the incidence angles of image-1 and image-2, respectively, the quantity…”

Section: The Input Datamentioning

confidence: 99%

An algorithm for operational flood mapping from Synthetic Aperture Radar (SAR) data using fuzzy logic

Pulvirenti

Pierdicca

Chini

et al. 2011

Nat. Hazards Earth Syst. Sci.

232

140

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Abstract. An algorithm developed to map flooded areas from synthetic aperture radar imagery is presented in this paper. It is conceived to be inserted in the operational flood management system of the Italian Civil Protection and can be used in an almost automatic mode or in an interactive mode, depending on the user's needs. The approach is based on the fuzzy logic that is used to integrate theoretical knowledge about the radar return from inundated areas taken into account by means of three electromagnetic scattering models, with simple hydraulic considerations and contextual information. This integration aims at allowing a user to cope with situations, such as the presence of vegetation in the flooded area, in which inundation mapping from satellite radars represents a difficult task. The algorithm is designed to work with radar data at L, C, and X frequency bands and employs also ancillary data, such as a land cover map and a digital elevation model. The flood mapping procedure is tested on an inundation that occurred in Albania on January 2010 using COSMO-SkyMed very high resolution X-band SAR data.

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“…The water/land contrast is of particular interest in the case of SWOT, because we need to automatically detect the continental water surfaces in HR mode and because it has an impact on the consequences of layover 4,5 . Based on Ulaby's measurements 6 , the Ka-band backscattering from water is expected to be much stronger than that of land surfaces for near-nadir viewing (of the order of 10 dB stronger in the incidence range of SWOT). However, these measurements are only representative of particular combinations of surface characteristics (roughness, soil humidity and composition, …).…”

Section: Modeling Of Radar Cross-section Of Natural Surfacesmentioning

confidence: 99%

KaRIn on SWOT: modeling and simulation of near-nadir Ka-band interferometric SAR images

et al. 2010

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The principal instrument of the wide-swath altimetry mission SWOT is KaRIn, a Ka-band interferometric SAR system operating on near-nadir swaths on both sides of the satellite track. Due to the short wavelength and particular observation geometry, there are very limited reports on the backscattering from natural surfaces. Simulators that cover both radiometric and geometric aspects are therefore developed in the framework of the CNES phase 0 and A studies of SWOT. This article presents the modeling and simulation approaches that have been adopted, and shows some preliminary simulation results.

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Millimeter Wave Measurement and Modeling of Terrain Scattering

Abstract: The view, opinions and/or findings contained in this report are those of the author(s) and should not be construed as an official Department of the Army position, policy, or decision, unless so designated by other documentation. 12a. DISTRIBUTION/AVAILABILITY STATEMENT

Cited by 20 publications

References 20 publications

94 GHz radar mapping of terrestrial snow cover

94 GHz radar mapping of terrestrial snow cover

An algorithm for operational flood mapping from Synthetic Aperture Radar (SAR) data using fuzzy logic

KaRIn on SWOT: modeling and simulation of near-nadir Ka-band interferometric SAR images

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