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Application of Shore-Based, Sky-Based and Marine Radars to Ocean and...
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Application of Shore-Based, Sky-Based and Marine Radars to Ocean and Target Parameter Extraction

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ocean Remote Sensing".

Deadline for manuscript submissions: 31 August 2024 | Viewed by 3870

Special Issue Editors

Dr. Reza Shahidi

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, Memorial University, St. John’s, NL, Canada
Interests: HF radar; ocean wave parameter and spectrum extraction; digital signal processing
Prof. Dr. Eric Gill

E-Mail Website
Guest Editor
Electrical Engineering Computer Engineering, Faculty of Engineering and Applied Science, St. John’s, NL, Canada
Interests: high frequency (HF) radiation; HF surface wave radar (HFSWR)

Special Issue Information

Dear Colleagues,

Over 65 years ago, Crombie observed the backscatter from HF radar transmitting at 13.5 MHz from the ocean surface and observed two dominant peaks in the Doppler spectrum, which were caused by Bragg scattering. Since that time, radar has often been used ocean monitoring, with new methodologies being introduced to extract ocean wave spectra and tide and wind information from backscattered radar data. In addition to HF radar, marine radar often operating at X-band frequencies have been used to monitor oceanographic parameters at higher resolutions, but usually over shorter ranges. Both radar modalities may also be used to monitor the presence of targets, such as ships or ice, in the ocean, as well as exact parameters of these targets, such as size, speed, and location.

This Special Issue aims to present new and cutting-edge research in the monitoring of targets such as ships and ice and their oceanographic parameters using various radar configurations, including sky-based radar and hardware. It also aims to collate new signal processing algorithms and methodologies to improve the accuracy of ocean surface and target parameter extraction data acquired using such radar systems.

Dr. Reza Shahidi
Prof. Dr. Eric Gill
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • HF radar
  • X-band radar
  • ocean wave parameters
  • doppler spectrum
  • target parameters
  • wave spectrum inversion
  • ocean surface currents
  • ocean surface winds

Published Papers (4 papers)

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Research

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22 pages, 7183 KiB  
Article
A Grid-Based Gradient Descent Extended Target Clustering Method and Ship Target Inverse Synthetic Aperture Radar Imaging for UHF Radar
by Lizun Zhang, Hao Zhou, Liyun Bai and Yingwei Tian
Remote Sens. 2023, 15(23), 5466; https://doi.org/10.3390/rs15235466 - 23 Nov 2023
Viewed by 689
Abstract
Inland shipping is of great significance in economic development, and ship surveillance and classification are of great importance for ship management and dispatch. For river ship detection, ultrahigh-frequency (UHF) radar is an effective equipment owing to its wide coverage and easy deployment. The [...] Read more.
Inland shipping is of great significance in economic development, and ship surveillance and classification are of great importance for ship management and dispatch. For river ship detection, ultrahigh-frequency (UHF) radar is an effective equipment owing to its wide coverage and easy deployment. The extension in range, Doppler, and azimuth and target recognition are two main problems in UHF ship detection. Clustering is a necessary step to get the center of an extended target. However, it is difficult to distinguish between different target echoes when they overlap each other in range, Doppler, and azimuth and so far practical methods for extended target recognition with UHF radar have been rarely discussed. In this study, a two-stage target classification method is proposed for UHF radar ship detection. In the first stage, grid-based gradient descent (GBGD) clustering is proposed to distinguish targets with three-dimensional (3D) information. Then in the second stage, the inverse synthetic aperture radar (ISAR) imaging algorithm is employed to differentiate ships of different types. The simulation results show that the proposed method achieves a 20% higher clustering accuracy than other methods when the targets have close 3D information. The feasibility of ISAR imaging for target classification using UHF radar is also validated via simulation. Some experimental results are also given to show the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Application of Shore-Based, Sky-Based and Marine Radars to Ocean and Target Parameter Extraction)
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20 pages, 5160 KiB  
Article
Sea Clutter Suppression Using Smoothed Pseudo-Wigner–Ville Distribution–Singular Value Decomposition during Sea Spikes
by Guigeng Li, Hao Zhang, Yong Gao and Bingyan Ma
Remote Sens. 2023, 15(22), 5360; https://doi.org/10.3390/rs15225360 - 15 Nov 2023
Viewed by 879
Abstract
The detection of small targets within the background of sea clutter is a significant challenge faced in radar signal processing. Small target echoes are weak in energy, and can be submerged by sea clutter and sea spikes, which are caused by overturning waves [...] Read more.
The detection of small targets within the background of sea clutter is a significant challenge faced in radar signal processing. Small target echoes are weak in energy, and can be submerged by sea clutter and sea spikes, which are caused by overturning waves and breaking waves. This severely affects the radar target detection performance. This paper proposes a smoothed pseudo-Wigner–Ville distribution–singular value decomposition (SPWVD-SVD) method for sea clutter suppression. This method determines the instantaneous frequency range of the target by contrasting the time–frequency characteristics of the sea spike and the target. Subsequently, it employs a singular value difference spectrum to reduce the rank of the Hankel matrix, thereby reducing the computational burden of the instantaneous frequency estimation step in the experiment. Based on the instantaneous frequency range of the target in the time–frequency domain, the singular values of the target signal are retained, while the singular values of clutter are set to zero. This process accomplishes the reconstruction of radar echo signals and effectively achieves the suppression of sea clutter. The suppression effect is verified using simulation data alongside ten sets of Intelligent Pixel processing X-band (IPIX) radar data against the background of sea spikes. By contrasting the clutter amplitudes before and after suppression, the SPWVD-SVD algorithm demonstrated an average clutter suppression of 15.06 dB, which proves the effectiveness of the proposed algorithm in suppressing sea clutter. Full article
(This article belongs to the Special Issue Application of Shore-Based, Sky-Based and Marine Radars to Ocean and Target Parameter Extraction)
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20 pages, 7148 KiB  
Article
Wind Direction Extraction from X-Band Marine Radar Images Based on the Attenuation Horizontal Component
by Huanyu Yu, Zhizhong Lu and Hui Wang
Remote Sens. 2023, 15(16), 3959; https://doi.org/10.3390/rs15163959 - 10 Aug 2023
Viewed by 948
Abstract
This paper presents a novel algorithm based on the attenuation horizontal component for wind direction retrieval from X-band marine radar images. The range dependence of radar return on the ocean surface can be presented in radar images, and the radar return decreases with [...] Read more.
This paper presents a novel algorithm based on the attenuation horizontal component for wind direction retrieval from X-band marine radar images. The range dependence of radar return on the ocean surface can be presented in radar images, and the radar return decreases with the increase in range. The traditional curve-fitting method averages the radar return of the whole range to retrieve the wind direction, but it is vulnerable to the interference of fixed objects and long-range low-intensity pixel points. For the pixels with the same range in the polar coordinates of the radar image, the ideal range attenuation model is derived by selecting the pixels with the highest intensity value. The ideal attenuation model is used to fit the attenuation data and calculate the attenuation horizontal component at each azimuth direction. To eliminate the effect of outliers, the iterative optimization method is used in the estimation of the attenuation horizontal component and the weights of the data are continuously updated. Finally, the wind direction is determined based on the azimuthal dependence of the attenuation horizontal component. This algorithm was tested using shipboard radar images and anemometer data collected in the East China Sea. The results show that, compared with the single curve-fitting method, the proposed algorithm can improve the wind direction retrieval accuracy in the case of more fixed targets. Under the condition of more fixed targets, the deviation and root mean square error are reduced by 16.3° and 16.2°, respectively. Full article
(This article belongs to the Special Issue Application of Shore-Based, Sky-Based and Marine Radars to Ocean and Target Parameter Extraction)
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17 pages, 10872 KiB  
Technical Note
A Floating Small Target Identification Method Based on Doppler Time Series Information
by Hengli Yu, Hao Ding, Zheng Cao, Ningbo Liu, Guoqing Wang and Zhaoxiang Zhang
Remote Sens. 2024, 16(3), 505; https://doi.org/10.3390/rs16030505 - 28 Jan 2024
Viewed by 684
Abstract
Traditional radar detection methods heavily rely on the signal-to-clutter ratio (SCR); a variety of feature-based detection methods have been proposed, providing a new way for radar detection and the recognition of weak targets. Existing feature-based detection methods determine the presence or absence of [...] Read more.
Traditional radar detection methods heavily rely on the signal-to-clutter ratio (SCR); a variety of feature-based detection methods have been proposed, providing a new way for radar detection and the recognition of weak targets. Existing feature-based detection methods determine the presence or absence of a target based on whether the feature value is within the judgment region, generally focusing only on the distribution of features and making insufficient use of inter-feature chronological information. This paper uses the autoregressive (AR) model to model and predict the time sequence of radar echoes in the feature domain and takes the chronological information of historical frame features as the prior information to form new features for detection on this basis. A classification method for floating small targets based on the Doppler spectrum centroid sequence is proposed. By using the AR model to fit the Doppler spectrum centroid feature sequence of the target, the model coefficients are regarded as the secondary features for target identification. The measured data show that the correct classification and identification rate of this method for ship targets and floating small targets can reach over 92% by using 50 centroid features. Full article
(This article belongs to the Special Issue Application of Shore-Based, Sky-Based and Marine Radars to Ocean and Target Parameter Extraction)
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