Special Issue "Radar and Sonar Imaging and Processing"

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

Deadline for manuscript submissions: 31 December 2019.

Special Issue Editors

Guest Editor
Prof. Dr. Andrzej Stateczny Website E-Mail
Department of Geodesy, Faculty of Civil and Environmental Engineering, Gdansk Technical University, Narutowicza St. 11/12, Gdansk, Poland
Interests: radar navigation; comparative (terrain reference) navigation; multisensor data fusion; automotive navigation, radar and sonar target detection, and tracking; sonar imaging and understanding; MBES bathymetry; autonomous navigation; Artificial Intelligence for navigation; deep learning; geoinformatics, underwater navigation
Guest Editor
Prof. Dr. Krzysztof Kulpa Website E-Mail
Institute of Electronic Systems, Warsaw University of Technology, Nowowiejska 15/19, Warszawa 00-665 Poland
Interests: Radar signal processing; cognitive radar and EW; radar imaging (SAR, ISAR); NCTR; detection and tracking
Guest Editor
Dr. Witold Kazimierski Website E-Mail
Institute of Geoinformatics, Faculty of Navigation, Maritime University of Szczecin, Waly Chrobrego 1-2, 70-500 Szczecin, Poland
Interests: target tracking; data fusion; maritime radars; spatial analysis; artificial neural networks; mobile cartography

Special Issue Information

Dear Colleagues,

Over the past years, radar and sonar technology has been at the center of several major developments in remote sensing both in civilian and defense applications. Although radar technology has been known for more than 100 years, it is still developing and it is now implemented in many maritime, air, satellite, and land applications. New technologies such as sparse image reconstruction and multistatic active and passive SAR and ISAR imaging are changing the quality of images and areas of applications. The rapid development of automotive radars in 3D dimensions, able to recognize different objects and assign the risk of collision, is one example of the progress of this technology. In maritime radars, the application of FMCW technology is becoming more and more popular, aside from classical pulse radars. Simultaneously, sonar technology has also been used for dozens of decades, at the beginning only for military solutions but, today, using 3D versions, it is used for many underwater tasks, such as underwater surface imaging, target detections, and tracking, among others. The impact of sonar technologies has been growing, particularly at the beginning of autonomous vehicles era. Recently, the influence of artificial intelligence for radar and sonar image processing and understanding has emerged. Radar and sonar systems are mounted onboard of smart and flexible platforms and also on several types of unmanned vehicles. Both of these technologies focus on remote detection of targets and both may encounter many common scientific challenges. Unfortunately, specialists from the radar and sonar fields do not interact with each other, slowing down progress in both areas.

This Special Issue will report the latest advances and trends in the field of remote sensing for radar and sonar image processing, addressing original developments, new applications, and practical solutions to open questions. The aim is to increase the data and knowledge exchange between those two communities and allow experts from other areas to understand the radar and sonar problems. Topics for this Special Issue include, but are not limited to, the following:

  • Passive and active radar imaging (SAR, ISAR)
  • Passive, bistatic, and multi-static radar imaging
  • 3D radar and 3D sonar imaging
  • Sonar image processing, data reduction, feature extraction, and image understanding
  • Interferometric methods
  • Sparse image reconstruction
  • Automatic target detection and classification
  • Radar sensors design and platform developments
  • Radar and sonar target tracking and anti-collision algorithms and methods
  • Multi-sensor data fusion
  • Synergy between radar, sonar, and other sensors
  • Radar and sonar base autonomous navigation
  • Ground Penetrating Radar application in civil engineering
  • Automotive and maritime radar
  • Radar and sonar surveillance systems
  • Side scan sonar, imaging sonar, chirp sonar, and forward-looking sonar
  • Artificial Intelligence for radar and sonar data processing
Prof. Dr. Andrzej Stateczny
Prof. Dr. Krzysztof Kulpa
Dr. Witold Kazimierski
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 papers will be 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 1800 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

  • radar
  • sonar
  • data fusion
  • sensors design
  • target tracking
  • target imaging
  • image understanding and target recognition

Published Papers (11 papers)

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Research

Open AccessArticle
Efficient Algorithm for SAR Refocusing of Ground Fast-Maneuvering Targets
Remote Sens. 2019, 11(19), 2214; https://doi.org/10.3390/rs11192214 - 22 Sep 2019
Abstract
The synthetic aperture radar (SAR) image of moving targets will defocus due to the unknown motion parameters. For fast-maneuvering targets, the range cell migration (RCM), Doppler frequency migration and Doppler ambiguity are complex problems. As a result, focusing of fast-maneuvering targets is difficult. [...] Read more.
The synthetic aperture radar (SAR) image of moving targets will defocus due to the unknown motion parameters. For fast-maneuvering targets, the range cell migration (RCM), Doppler frequency migration and Doppler ambiguity are complex problems. As a result, focusing of fast-maneuvering targets is difficult. In this work, an efficient SAR refocusing algorithm is proposed for fast-maneuvering targets. The proposed algorithm mainly contains three steps. Firstly, the RCM is corrected using sequence reversing, matrix complex multiplication and an improved second-order RCM correction function. Secondly, a 1D scaled Fourier transform is introduced to estimate the remaining chirp rate. Thirdly, a matched filter based on the estimated chirp rate is proposed to focus the maneuvering target in the range–azimuth time domain. The proposed method is computationally efficient because it can be implemented by the fast Fourier transform (FFT), inverse FFT and non-uniform FFT. A new deramp function is proposed to further address the serious problem of Doppler ambiguity. A spurious peak recognition procedure is proposed on the basis of the cross-term analysis. Simulated and real data processing results demonstrate the validity of the proposed target focusing algorithm and spurious peak recognition procedure. Full article
(This article belongs to the Special Issue Radar and Sonar Imaging and Processing)
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Open AccessArticle
An Improved Generalized Chirp Scaling Algorithm Based on Lagrange Inversion Theorem for High-Resolution Low Frequency Synthetic Aperture Radar Imaging
Remote Sens. 2019, 11(16), 1874; https://doi.org/10.3390/rs11161874 - 10 Aug 2019
Abstract
The high-resolution low frequency synthetic aperture radar (SAR) has serious range-azimuth phase coupling due to the large bandwidth and long integration time. High-resolution SAR processing methods are necessary for focusing the raw data of such radar. The generalized chirp scaling algorithm (GCSA) is [...] Read more.
The high-resolution low frequency synthetic aperture radar (SAR) has serious range-azimuth phase coupling due to the large bandwidth and long integration time. High-resolution SAR processing methods are necessary for focusing the raw data of such radar. The generalized chirp scaling algorithm (GCSA) is generally accepted as an attractive solution to focus SAR systems with low frequency, large bandwidth and wide beam bandwidth. However, as the bandwidth and/or beamwidth increase, the serious phase coupling limits the performance of the current GCSA and degrades the imaging quality. The degradation is mainly caused by two reasons: the residual high-order coupling phase and the non-negligible error introduced by the linear approximation of stationary phase point using the principle of stationary phase (POSP). According to the characteristics of a high-resolution low frequency SAR signal, this paper firstly presents a principle to determine the required order of range frequency. After compensating for the range-independent coupling phase above 3rd order, an improved GCSA based on Lagrange inversion theorem is analytically derived. The Lagrange inversion enables the high-order range-dependent coupling phase to be accurately compensated. Imaging results of P- and L-band SAR data demonstrate the excellent performance of the proposed algorithm compared to the existing GCSA. The image quality and focusing depth in range dimension are greatly improved. The improved method provides the possibility to efficiently process high-resolution low frequency SAR data with wide swath. Full article
(This article belongs to the Special Issue Radar and Sonar Imaging and Processing)
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Open AccessArticle
Analytical Approximation Model for Quadratic Phase Error Introduced by Orbit Determination Errors in Real-Time Spaceborne SAR Imaging
Remote Sens. 2019, 11(14), 1663; https://doi.org/10.3390/rs11141663 - 12 Jul 2019
Abstract
Research on real-time spaceborne synthetic aperture radar (SAR) imaging has emerged as satellite computation capability has increased and applications of SAR imaging products have expanded. The orbit determination data of a spaceborne SAR platform are essential for the SAR imaging procedure. In real-time [...] Read more.
Research on real-time spaceborne synthetic aperture radar (SAR) imaging has emerged as satellite computation capability has increased and applications of SAR imaging products have expanded. The orbit determination data of a spaceborne SAR platform are essential for the SAR imaging procedure. In real-time SAR imaging, onboard orbit determination data cannot achieve a level of accuracy that is equivalent to the orbit ephemeris in ground-based SAR processing, which requires a long processing time using common ground-based SAR imaging procedures. It is important to study the influence of errors in onboard real-time orbit determination data on SAR image quality. Instead of the widely used numerical simulation method, an analytical approximation model of the quadratic phase error (QPE) introduced by orbit determination errors is proposed. The proposed model can provide approximation results at two granularities: approximations with a satellite’s true anomaly as the independent variable and approximations for all positions in the satellite’s entire orbit. The proposed analytical approximation model reduces simulation complexity, extent of calculations, and the processing time. In addition, the model reveals the core of the process by which errors are transferred to QPE calculations. A detailed comparison between the proposed method and a numerical simulation method proves the correctness and reliability of the analytical approximation model. With the help of this analytical approximation model, the technical parameter iteration procedure during the early-stage development of an onboard real-time SAR imaging mission will likely be accelerated. Full article
(This article belongs to the Special Issue Radar and Sonar Imaging and Processing)
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Open AccessArticle
Obtaining High-Resolution Seabed Topography and Surface Details by Co-Registration of Side-Scan Sonar and Multibeam Echo Sounder Images
Remote Sens. 2019, 11(12), 1496; https://doi.org/10.3390/rs11121496 - 24 Jun 2019
Cited by 1
Abstract
Side-scan sonar (SSS) is used for obtaining high-resolution seabed images, but with low position accuracy without using the Ultra Short Base Line (USBL) or Short Base Line (SBL). Multibeam echo sounder (MBES), which can simultaneously obtain high-accuracy seabed topography as well as seabed [...] Read more.
Side-scan sonar (SSS) is used for obtaining high-resolution seabed images, but with low position accuracy without using the Ultra Short Base Line (USBL) or Short Base Line (SBL). Multibeam echo sounder (MBES), which can simultaneously obtain high-accuracy seabed topography as well as seabed images with low resolution in deep water. Based on the complementarity of SSS and MBES data, this paper proposes a new method for acquiring high-resolution seabed topography and surface details that are difficult to obtain using MBES or SSS alone. Firstly, according to the common seabed features presented in both images, the Speeded-Up Robust Features (SURF) algorithm, with the constraint of image geographic coordinates, is adopted for initial image matching. Secondly, to further improve the matching performance, a template matching strategy using the dense local self-similarity (DLSS) descriptor is adopted according to the self-similarities within these two images. Next, the random sample consensus (RANSAC) algorithm is used for removing the mismatches and the SSS backscatter image geographic coordinates are rectified by the transformation model established based on the correct matched points. Finally, the superimposition of this rectified SSS backscatter image on MBES seabed topography is performed and the high-resolution and high-accuracy seabed topography and surface details can be obtained. Full article
(This article belongs to the Special Issue Radar and Sonar Imaging and Processing)
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Open AccessArticle
A Gray Scale Correction Method for Side-Scan Sonar Images Based on Retinex
Remote Sens. 2019, 11(11), 1281; https://doi.org/10.3390/rs11111281 - 29 May 2019
Cited by 1
Abstract
When side-scan sonars collect data, sonar energy attenuation, the residual of time varying gain, beam patterns, angular responses, and sonar altitude variations occur, which lead to an uneven gray level in side-scan sonar images. Therefore, gray scale correction is needed before further processing [...] Read more.
When side-scan sonars collect data, sonar energy attenuation, the residual of time varying gain, beam patterns, angular responses, and sonar altitude variations occur, which lead to an uneven gray level in side-scan sonar images. Therefore, gray scale correction is needed before further processing of side-scan sonar images. In this paper, we introduce the causes of gray distortion in side-scan sonar images and the commonly used optical and side-scan sonar gray scale correction methods. As existing methods cannot effectively correct distortion, we propose a simple, yet effective gray scale correction method for side-scan sonar images based on Retinex given the characteristics of side-scan sonar images. Firstly, we smooth the original image and add a constant as an illumination map. Then, we divide the original image by the illumination map to produce the reflection map. Finally, we perform element-wise multiplication between the reflection map and a constant coefficient to produce the final enhanced image. Two different schemes are used to implement our algorithm. For gray scale correction of side-scan sonar images, the proposed method is more effective than the latest similar methods based on the Retinex theory, and the proposed method is faster. Experiments prove the validity of the proposed method. Full article
(This article belongs to the Special Issue Radar and Sonar Imaging and Processing)
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Open AccessArticle
Estimation of Translational Motion Parameters in Terahertz Interferometric Inverse Synthetic Aperture Radar (InISAR) Imaging Based on a Strong Scattering Centers Fusion Technique
Remote Sens. 2019, 11(10), 1221; https://doi.org/10.3390/rs11101221 - 23 May 2019
Abstract
Translational motion of a target will lead to image misregistration in interferometric inverse synthetic aperture radar (InISAR) imaging. In this paper, a strong scattering centers fusion (SSCF) technique is proposed to estimate translational motion parameters of a maneuvering target. Compared to past InISAR [...] Read more.
Translational motion of a target will lead to image misregistration in interferometric inverse synthetic aperture radar (InISAR) imaging. In this paper, a strong scattering centers fusion (SSCF) technique is proposed to estimate translational motion parameters of a maneuvering target. Compared to past InISAR image registration methods, the SSCF technique is advantageous in its high computing efficiency, excellent antinoise performance, high registration precision, and simple system structure. With a one-input three-output terahertz InISAR system, translational motion parameters in both the azimuth and height direction are precisely estimated. Firstly, the motion measurement curves are extracted from the spatial spectrums of mutually independent strong scattering centers, which avoids the unfavorable influences of noise and the “angle scintillation” phenomenon. Then, the translational motion parameters are obtained by fitting the motion measurement curves with phase unwrapping and intensity-weighted fusion processing. Finally, ISAR images are registered precisely by compensating the estimated translational motion parameters, and high-quality InISAR imaging results are achieved. Both simulation and experimental results are used to verify the validity of the proposed method. Full article
(This article belongs to the Special Issue Radar and Sonar Imaging and Processing)
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Open AccessFeature PaperArticle
The Empirical Application of Automotive 3D Radar Sensor for Target Detection for an Autonomous Surface Vehicle’s Navigation
Remote Sens. 2019, 11(10), 1156; https://doi.org/10.3390/rs11101156 - 14 May 2019
Abstract
Avoiding collisions with other objects is one of the most basic safety tasks undertaken in the operation of floating vehicles. Addressing this challenge is essential, especially during unmanned vehicle navigation processes in autonomous missions. This paper provides an empirical analysis of the surface [...] Read more.
Avoiding collisions with other objects is one of the most basic safety tasks undertaken in the operation of floating vehicles. Addressing this challenge is essential, especially during unmanned vehicle navigation processes in autonomous missions. This paper provides an empirical analysis of the surface target detection possibilities in a water environment, which can be used for the future development of tracking and anti-collision systems for autonomous surface vehicles (ASV). The research focuses on identifying the detection ranges and the field of view for various surface targets. Typical objects that could be met in the water environment were analyzed, including a boat and floating objects. This study describes the challenges of implementing automotive radar sensors for anti-collision tasks in a water environment from the perspective of target detection with the application for small ASV performing tasks on the lake. Full article
(This article belongs to the Special Issue Radar and Sonar Imaging and Processing)
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Open AccessArticle
On the Reliability of Surface Current Measurements by X-Band Marine Radar
Remote Sens. 2019, 11(9), 1030; https://doi.org/10.3390/rs11091030 - 30 Apr 2019
Abstract
Real-time quality-controlled surface current data derived from X-Band marine radar (MR) measurements were evaluated to estimate their operational reliability. The presented data were acquired by the standard commercial off-the-shelf MR-based sigma s6 WaMoS® II (WaMoS® II) deployed onboard the [...] Read more.
Real-time quality-controlled surface current data derived from X-Band marine radar (MR) measurements were evaluated to estimate their operational reliability. The presented data were acquired by the standard commercial off-the-shelf MR-based sigma s6 WaMoS® II (WaMoS® II) deployed onboard the German Research vessel Polarstern. The measurement reliability is specified by an IQ value obtained by the WaMoS® II real-time quality control (rtQC). Data which pass the rtQC without objection are assumed to be reliable. For these data sets accuracy and correlation with corresponding vessel-mounted acoustic Doppler current profiler (ADCP) measurements are determined. To reduce potential misinterpretation due to short-term oceanic variability/turbulences, the evaluation of the WaMoS® II accuracy was carried out based on sliding means over 20 min of the reliable data only. The associated standard deviation σ W a M o S = 0.02 m/s of the mean WaMoS® II measurements reflect a high precision of the measurement and the successful rtQC during different wave, current and weather conditions. The direct comparison of 7272 WaMoS® II/ADCP northward and eastward velocity data pairs yield a correlation of r   0.94 , with | b i a s Δ |   0.06 m/s and σ S = 0.05 m/s. This confirms that the MR-based surface current measurements are accurate and reliable. Full article
(This article belongs to the Special Issue Radar and Sonar Imaging and Processing)
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Open AccessArticle
An Imaging Algorithm for Multireceiver Synthetic Aperture Sonar
Remote Sens. 2019, 11(6), 672; https://doi.org/10.3390/rs11060672 - 20 Mar 2019
Abstract
For the multireceiver synthetic aperture sonar (SAS), the point target reference spectrum (PTRS) in the two-dimensional (2D) frequency domain and azimuth modulation in the range Doppler domain were first deduced based on a numerical evaluation method and accurate time delay. Then, the difference [...] Read more.
For the multireceiver synthetic aperture sonar (SAS), the point target reference spectrum (PTRS) in the two-dimensional (2D) frequency domain and azimuth modulation in the range Doppler domain were first deduced based on a numerical evaluation method and accurate time delay. Then, the difference between the PTRS and azimuth modulation generated the coupling term in the 2D frequency domain. Compared with traditional methods, the PTRS, azimuth modulation and coupling term was better at avoiding approximations. Based on three functions, an imaging algorithm is presented in this paper. Considering the fact that the coupling term is characterized by range variance, the range-dependent sub-block processing method was exploited to perform the decoupling. Simulation results showed that the presented method improved the imaging performance across the whole swath in comparison with existing multireceiver SAS processor. Furthermore, real data was used to validate the presented method. Full article
(This article belongs to the Special Issue Radar and Sonar Imaging and Processing)
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Open AccessArticle
An Adaptive Denoising and Detection Approach for Underwater Sonar Image
Remote Sens. 2019, 11(4), 396; https://doi.org/10.3390/rs11040396 - 15 Feb 2019
Cited by 1
Abstract
An adaptive approach is proposed to denoise and detect the underwater sonar image in this paper. Firstly, to improve the denoising performance of non-local spatial information in the underwater sonar image, an adaptive non-local spatial information denoising method based on the golden ratio [...] Read more.
An adaptive approach is proposed to denoise and detect the underwater sonar image in this paper. Firstly, to improve the denoising performance of non-local spatial information in the underwater sonar image, an adaptive non-local spatial information denoising method based on the golden ratio is proposed. Then, a new adaptive cultural algorithm (NACA) is proposed to accurately and quickly complete the underwater sonar image detection in this paper. Concretely, NACA has two improvements. In the first place, to obtain better initial clustering centres, an adaptive initialization algorithm based on data field (AIA-DF) is proposed in this paper. Secondly, in the belief space of NACA, a new update strategy is adopted to update cultural individuals in terms of the quantum-inspired shuffled frog leaping algorithm (QSFLA). The experimental results show that the proposed denoising method in this paper can effectively remove relatively large and small filtering degree parameters and improve the denoising performance to some extent. Compared with other comparison algorithms, the proposed NACA can converge to the global optimal solution within small epochs and accurately complete the object detection, having better effectiveness and adaptability. Full article
(This article belongs to the Special Issue Radar and Sonar Imaging and Processing)
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Open AccessArticle
Comparison of Computational Intelligence Methods Based on Fuzzy Sets and Game Theory in the Synthesis of Safe Ship Control Based on Information from a Radar ARPA System
Remote Sens. 2019, 11(1), 82; https://doi.org/10.3390/rs11010082 - 04 Jan 2019
Cited by 1
Abstract
This article presents safe ship control optimization design for navigator advisory system. Optimal safe ship control is presented as multistage decision-making in a fuzzy environment and as multistep decision-making in a game environment. The navigator’s subjective and the maneuvering parameters are taken under [...] Read more.
This article presents safe ship control optimization design for navigator advisory system. Optimal safe ship control is presented as multistage decision-making in a fuzzy environment and as multistep decision-making in a game environment. The navigator’s subjective and the maneuvering parameters are taken under consideration in the model process. A computer simulation of fuzzy neural anticollision (FNAC) and matrix game anticollision (MGAC) algorithms was carried out on MATLAB software on an example of the real navigational situation of passing three encountered ships in the Skagerrak Strait, in good and restricted visibility at sea. The developed solution can be applied in decision-support systems on board a ship. Full article
(This article belongs to the Special Issue Radar and Sonar Imaging and Processing)
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