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Radar Ocean Remote Sensing
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Radar Ocean Remote Sensing

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: closed (20 May 2022) | Viewed by 17580

Special Issue Editors

Dr. David Lyzenga

E-Mail Website
Guest Editor
Department of Naval Architecture and Marine Engineering, University of Michigan, Ann Arbor, MI 48109, USA
Interests: ocean remote sensing; small-scale surface hydrodynamics; interaction of electromagnetic radiation with the ocean
Prof. Dr. Biao Zhang

E-Mail Website
Guest Editor
School of Marine Sciences, Nanjing University of Information Science and Technology, 219 Ningliu Road, Nanjing 210044, China
Interests: satellite oceanography; tropical cyclone remote sensing; atmosphere-ocean interaction; radar constellation sea ice monitoring; marine information intelligent extraction
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Radio waves have been used to probe the ocean for many years, starting with HF radar observations by Crombie in 1955. Other forms of electromagnetic radiation, including both naturally occurring and synthetically generated waves in the optical, infrared, and microwave regions of the spectrum, have also been used to great advantage in remotely observing various properties and processes in the ocean. Microwave radiation has received special attention because of its ability to resolve relatively small features and because it interacts directly with short-scale surface waves that are influenced by winds and currents. Microwave radiation is also relatively uninfluenced by the atmosphere and is amenable to generation and observation by earth satellites. This Special Issue will focus on recent developments in remote sensing of the ocean using active microwave techniques. We would like to encourage submissions in all areas including instrument development, surface scattering theory and observations, and information extraction algorithms. Studies using various measurement platforms including satellites, aircraft, ships, and land-based equipment are of interest.

Dr. David Lyzenga
Prof. Dr. Biao Zhang
Guest Editors

Manuscript Submission Information

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Keywords

  • Radar
  • Ocean remote sensing
  • Physical oceanography
  • Electromagnetic radiation

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Published Papers (6 papers)

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Research

18 pages, 12570 KiB  
Article
SAR Imaging Algorithm of Ocean Waves Based on Optimum Subaperture
by Yawei Zhao, Xianen Wei, Jinsong Chong and Lijie Diao
Sensors 2022, 22(3), 1299; https://doi.org/10.3390/s22031299 - 8 Feb 2022
Cited by 1 | Viewed by 2839
Abstract
Synthetic Aperture Radar (SAR) is widely applied to the field of ocean remote sensing. Clear SAR images are the basis for ocean information acquisitions, such as parameter retrieval of ocean waves and wind field inversion of the ocean surface. However, the SAR ocean [...] Read more.
Synthetic Aperture Radar (SAR) is widely applied to the field of ocean remote sensing. Clear SAR images are the basis for ocean information acquisitions, such as parameter retrieval of ocean waves and wind field inversion of the ocean surface. However, the SAR ocean images are usually blurred, which seriously affects the acquisition of ocean information. The reasons for the wave blurring in SAR images mainly include the following two aspects. One is that when SAR observes the ocean, the motion of ocean waves will have a greater impact on imaging quality. The other is that the ocean’s surface is seriously decorrelated within the integration time. In order to obtain clear SAR images of ocean waves, a SAR imaging algorithm of ocean waves based on the optimum subaperture is proposed, aiming at the above two aspects. The optimum focus setting of the ocean waves is calculated, drawing support from the azimuth phase velocity of the dominant wave. The optimum subaperture is further calculated according to the proposed new evaluation, namely, F. Finally, according to the optimum focus setting and the optimum subaperture, the dominant wave is refocused, and a clear SAR image of the dominant wave can be obtained. The proposed algorithm was applied to airborne L-band and P-band SAR data. Furthermore, the proposed algorithm was compared with present methods, and the results sufficiently demonstrated the effectiveness and superiority of the proposed algorithm. Full article
(This article belongs to the Special Issue Radar Ocean Remote Sensing)
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26 pages, 7265 KiB  
Article
Physics-Based Forward Modeling of Ocean Surface Swell Effects on SMAP L1-C NRCS Observations
by Shanka N. Wijesundara and Joel T. Johnson
Sensors 2022, 22(2), 699; https://doi.org/10.3390/s22020699 - 17 Jan 2022
Viewed by 2134
Abstract
This paper examines the impact of ocean surface swell waves on near-coastal L-band high-resolution synthetic aperture radar (SAR) data collected using the National Aeronautics and Space Administration’s (NASA) Soil Moisture Active/Passive (SMAP) radar at 40° incidence angle. The two-scale model and a more [...] Read more.
This paper examines the impact of ocean surface swell waves on near-coastal L-band high-resolution synthetic aperture radar (SAR) data collected using the National Aeronautics and Space Administration’s (NASA) Soil Moisture Active/Passive (SMAP) radar at 40° incidence angle. The two-scale model and a more efficient off-nadir approximation of the second-order small-slope-approximation are used for co- and cross-polarized backscatter normalized radar cross-section (NRCS) predictions of the ocean surface, respectively. Backscatter NRCS predictions are modeled using a combined wind and swell model where wind-driven surface roughness is characterized using the Durden–Vesecky directional spectrum, while swell effects are represented through their contribution to the long wave slope variance (mean-square slopes, or MSS). The swell-only MSS is numerically computed based on a model defined using the JONSWAP spectrum with parameters calculated using the National Data Buoy Center and Wave Watch III data. The backscatter NRCS model is further refined to include fetch-limited and low-wind corrections. The results show an improved agreement between modeled and observed HH-polarized backscatter NRCS when swell effects are included and indicate a relatively larger swell impact on L-band compared to higher radar frequencies. Preliminary investigations into the potential swell retrieval capabilities in the form of excess MSS are encouraging, however further refinements are required to make broadly applicable conclusions. Full article
(This article belongs to the Special Issue Radar Ocean Remote Sensing)
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14 pages, 7400 KiB  
Article
A Coherent on Receive X-Band Marine Radar for Ocean Observations
by Jochen Horstmann, Jan Bödewadt, Ruben Carrasco, Marius Cysewski, Jörg Seemann and Michael Streβer
Sensors 2021, 21(23), 7828; https://doi.org/10.3390/s21237828 - 25 Nov 2021
Cited by 19 | Viewed by 4392
Abstract
Marine radars are increasingly popular for monitoring meteorological and oceanographic parameters such as ocean surface wind, waves and currents as well as bathymetry and shorelines. Within this paper a coherent on receive marine radar is introduced, which is based on an incoherent off [...] Read more.
Marine radars are increasingly popular for monitoring meteorological and oceanographic parameters such as ocean surface wind, waves and currents as well as bathymetry and shorelines. Within this paper a coherent on receive marine radar is introduced, which is based on an incoherent off the shelf pulsed X-band radar. The main concept of the coherentization is based on the coherent on receive principle, where the coherence is achieved by measuring the phase of the transmitted pulse from a leak in the radar circulator, which then serves as a reference phase for the transmitted pulse. The Doppler shift frequency can be computed from two consecutive pulse-pairs in the time domain or from the first moment of the Doppler spectrum inferred by means of a short time Fast Fourier Transform. From the Doppler shift frequencies, radial speed maps of the backscatter of the ocean surface are retrieved. The resulting backscatter intensity and Doppler speed maps are presented for horizontal as well as vertical polarization, and discussed with respect to meteorological and oceanographic applications. Full article
(This article belongs to the Special Issue Radar Ocean Remote Sensing)
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14 pages, 2370 KiB  
Article
Estimating Coastal Winds by Assimilating High-Frequency Radar Spectrum Data in SWAN
by Philip Muscarella, Kelsey Brunner and David Walker
Sensors 2021, 21(23), 7811; https://doi.org/10.3390/s21237811 - 24 Nov 2021
Cited by 6 | Viewed by 1889
Abstract
Many activities require accurate wind and wave forecasts in the coastal ocean. The assimilation of fixed buoy observations into spectral wave models such as SWAN (Simulating Waves Nearshore) can provide improved estimates of wave forecasts fields. High-frequency (HF) radar observations provide a spatially [...] Read more.
Many activities require accurate wind and wave forecasts in the coastal ocean. The assimilation of fixed buoy observations into spectral wave models such as SWAN (Simulating Waves Nearshore) can provide improved estimates of wave forecasts fields. High-frequency (HF) radar observations provide a spatially expansive dataset in the coastal ocean for assimilation into wave models. A forward model for the HF Doppler spectrum based on first- and second-order Bragg scattering was developed to assimilate the HF radar wave observations into SWAN. This model uses the spatially varying wave spectra computed using the SWAN model, forecast currents from the Navy Coastal Ocean Model (NCOM), and system parameters from the HF radar sites to predict time-varying range-Doppler maps. Using an adjoint of the HF radar model, the error between these predictions and the corresponding HF Doppler spectrum observations can be translated into effective wave-spectrum errors for assimilation in the SWAN model for use in correcting the wind forcing in SWAN. The initial testing and validation of this system have been conducted using data from ten HF radar sites along the Southern California Bight during the CASPER-West experiment in October 2017. The improved winds compare positively to independent observation data, demonstrating that this algorithm can be utilized to fill an observational gap in the coastal ocean for winds and waves. Full article
(This article belongs to the Special Issue Radar Ocean Remote Sensing)
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11 pages, 782 KiB  
Communication
Wave Measurements Using Multi-Frame Processing of Marine Radar Data
by David Lyzenga and Mirko Previsic
Sensors 2021, 21(16), 5639; https://doi.org/10.3390/s21165639 - 21 Aug 2021
Cited by 2 | Viewed by 2322
Abstract
Marine radars have proven to be useful for measuring ocean waves, but the accuracy of the measurements is limited by several factors including the look-angle dependence of the radar signals as well as noise in the radar data. The look-angle dependence introduces a [...] Read more.
Marine radars have proven to be useful for measuring ocean waves, but the accuracy of the measurements is limited by several factors including the look-angle dependence of the radar signals as well as noise in the radar data. The look-angle dependence introduces a systematic error or bias in the measurements, and noise causes a random error. This paper describes a method of combining data from multiple radar frames that is optimal in the sense of minimizing the error for a set of biased measurements with random additive noise. The results are shown experimentally to increase the correlation of the radar estimates with buoy measurements. Full article
(This article belongs to the Special Issue Radar Ocean Remote Sensing)
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21 pages, 8633 KiB  
Article
Microwave Specular Measurements and Ocean Surface Wave Properties
by Paul A. Hwang, Thomas L. Ainsworth and Jeffrey D. Ouellette
Sensors 2021, 21(4), 1486; https://doi.org/10.3390/s21041486 - 20 Feb 2021
Cited by 7 | Viewed by 2523
Abstract
Microwave reflectometers provide spectrally integrated information of ocean surface waves several times longer than the incident electromagnetic (EM) wavelengths. For high wind condition, it is necessary to consider the modification of relative permittivity by air in foam and whitecaps produced by wave breaking. [...] Read more.
Microwave reflectometers provide spectrally integrated information of ocean surface waves several times longer than the incident electromagnetic (EM) wavelengths. For high wind condition, it is necessary to consider the modification of relative permittivity by air in foam and whitecaps produced by wave breaking. This paper describes the application of these considerations to microwave specular returns from the ocean surface. Measurements from Ku and Ka band altimeters and L band reflectometers are used for illustration. The modeling yields a straightforward integration of a closed-form expression connecting the observed specular normalized radar cross section (NRCS) to the surface wave statistical and geometric properties. It remains a challenge to acquire sufficient number of high-wind collocated and simultaneous reference measurements for algorithm development or validation and verification effort. Solutions from accurate forward computation can supplement the sparse high wind databases. Modeled specular NRCSs are provided for L, C, X, Ku, and Ka bands with wind speeds up to 99 m/s. Full article
(This article belongs to the Special Issue Radar Ocean Remote Sensing)
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