E-Mail Alert

Add your e-mail address to receive forthcoming issues of this journal:

Journal Browser

Journal Browser

Special Issue "Synthetic Aperture Radar (SAR) Techniques and Applications"

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

Deadline for manuscript submissions: 30 June 2019

Special Issue Editor

Guest Editor
Dr. Fabio Bovenga

Research National Council of Italy - IREA, Via Amendola, 122/d, 70126 Bari, Italy
Website | E-Mail
Phone: +390805929425
Interests: advanced processing techniques for Synthetic Aperture Radar (SAR) imaging and SAR interferometry, and the application of multi-temporal/multi-frequencies analysis to ground monitoring

Special Issue Information

Dear Colleagues,

Synthetic Aperture RADAR (SAR) became a well-established and powerful remote sensing technology used worldwide for several applications thanks to the possibility of sensing the Earth surface at night and day and in any weather condition. Recent advances have dramatically raised on SAR monitoring potential by improving spatial resolution, revisit time, swath width, polarimetric capability. Moreover, the present and forthcoming space-borne missions allow SAR imaging at different bands and acquisition modes (e.g. spotlight, wide swath, bistatic, multistatic, geosynchronous). All these advances stimulated the investigation of new processing algorithms, products, and applications able to fully exploit new sensor capabilities (e.g. wide spectral band, short revisit time, multi-angle view), and the large SAR data archive.

Based on this, papers are requested, dealing with the following research issues concerning both algorithm developments and applicative examples:

  • Innovative SAR sensors, concepts, and acquisition modes;
  • innovative SAR products;
  • SAR signal modeling, simulation, and processing;
  • SAR imaging from Unmanned Aerial Vehicles (UAV), ground based sensors, and geosynchronous platforms;
  • advances in SAR polarimetry, SAR across/along track interferometry, and SAR tomography;
  • new opportunities for SAR applications to land, sea, and natural disasters.

Dr. Fabio Bovenga
Guest Editor

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. Sensors 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

  • New SAR sensors / concepts
  • New SAR acquisition modes
  • New SAR products
  • SAR image processing
  • SAR signal modeling and simulation
  • SAR imaging from Unmanned Aerial Vehicles (UAV)
  • Ground based SAR
  • Geosynchronous SAR
  • SAR polarimetry
  • Across / along track SAR interferometry
  • SAR tomography
  • SAR for land applications
  • SAR for sea applications
  • SAR for natural disasters

Published Papers (12 papers)

View options order results:
result details:
Displaying articles 1-12
Export citation of selected articles as:

Research

Open AccessArticle A Novel Multi-Angle SAR Imaging System and Method Based on an Ultrahigh Speed Platform
Sensors 2019, 19(7), 1701; https://doi.org/10.3390/s19071701
Received: 20 January 2019 / Revised: 31 March 2019 / Accepted: 3 April 2019 / Published: 10 April 2019
PDF Full-text (9621 KB) | HTML Full-text | XML Full-text
Abstract
Considering the difficulty of pulse repetition frequency (PRF) design in multi-angle SAR when using ultra-high speed platforms, a multi-angle SAR imaging system in a unified coordinate system is proposed. The digital multi-beamforming is used in the system and multi-angle SAR data can be [...] Read more.
Considering the difficulty of pulse repetition frequency (PRF) design in multi-angle SAR when using ultra-high speed platforms, a multi-angle SAR imaging system in a unified coordinate system is proposed. The digital multi-beamforming is used in the system and multi-angle SAR data can be obtained in one flight. Therefore, the system improves the efficiency of data recording. An improved range migration algorithm (RMA) is used for data processing, and imaging is made in a unified imaging coordinate system. The resolution of different view images is the same, and there is a fixed delay between the images. On this basis, the SAR image fusion is performed after image matching. The results of simulation and measured data confirm the effectiveness of the system and the method. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Techniques and Applications)
Figures

Figure 1

Open AccessArticle A Data-Driven Approach to SAR Data-Focusing
Sensors 2019, 19(7), 1649; https://doi.org/10.3390/s19071649
Received: 6 February 2019 / Revised: 29 March 2019 / Accepted: 4 April 2019 / Published: 6 April 2019
PDF Full-text (7075 KB) | HTML Full-text | XML Full-text
Abstract
Synthetic Aperture RADAR (SAR) is a radar imaging technique in which the relative motion of the sensor is used to synthesize a very long antenna and obtain high spatial resolution. Several algorithms for SAR data-focusing are well established and used by space agencies. [...] Read more.
Synthetic Aperture RADAR (SAR) is a radar imaging technique in which the relative motion of the sensor is used to synthesize a very long antenna and obtain high spatial resolution. Several algorithms for SAR data-focusing are well established and used by space agencies. Such algorithms are model-based, i.e., the radiometric and geometric information about the specific sensor must be well known, together with the ancillary data information acquired on board the platform. In the development of low-cost and lightweight SAR sensors, to be used in several application fields, the precise mission parameters and the knowledge of all the specific geometric and radiometric information about the sensor might complicate the hardware and software requirements. Despite SAR data processing being a well-established imaging technique, the proposed algorithm aims to exploit the SAR coherent illumination, demonstrating the possibility of extracting the reference functions, both in range and azimuth directions, when a strong point scatterer (either natural or manmade) is present in the scene. The Singular Value Decomposition is used to exploit the inherent redundancy present in the raw data matrix, and phase unwrapping and polynomial fitting are used to reconstruct clean versions of the reference functions. Fairly focused images on both synthetic and real raw data matrices without the knowledge of mission parameters and ancillary data information can be obtained; as a byproduct, azimuth beam pattern and estimates of a few other parameters have been extracted from the raw data itself. In a previous paper, authors introduced a preliminary work dealing with this problem and able to obtain good-quality images, if compared to the standard processing techniques. In this work, the proposed technique is described, and performance parameters are extracted to compare the proposed approach to RD, showing good adherence of the focused images and pulse responses. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Techniques and Applications)
Figures

Figure 1

Open AccessArticle Simulation and Analysis of SAR Images of Oceanic Shear-Wave-Generated Eddies
Sensors 2019, 19(7), 1529; https://doi.org/10.3390/s19071529
Received: 23 February 2019 / Revised: 16 March 2019 / Accepted: 26 March 2019 / Published: 29 March 2019
PDF Full-text (9314 KB) | HTML Full-text | XML Full-text
Abstract
Synthetic Aperture Radar (SAR) is widely used in oceanic eddies research. High-resolution SAR images should be useful in revealing eddy features and investigating the eddy imaging mechanism. However, SAR imaging is affected by various radar parameters and environmental factors, which makes it quite [...] Read more.
Synthetic Aperture Radar (SAR) is widely used in oceanic eddies research. High-resolution SAR images should be useful in revealing eddy features and investigating the eddy imaging mechanism. However, SAR imaging is affected by various radar parameters and environmental factors, which makes it quite difficult to learn directly from SAR eddy images. In order to interpret and evaluate eddy images, developing a proper simulation method is necessary. However, seldom has a SAR simulation method for oceanic eddies, especially for shear-wave-generated eddies, been established. As a step forward, we propose a simulation method for oceanic shear-wave-generated eddies. The Burgers-Rott vortex model is used to specify the surface current field of the simulated eddies. Images are then simulated for a range of different radar frequencies, radar look directions, wind speeds, and wind directions. The results show that the simulated images are consistent with actual SAR images. The effects of different radar parameters and wind fields on SAR eddy imaging are analyzed by qualitative and quantitative methods. Overall, the simulated images produce a surface pattern and brightness variations with characteristics resembling actual SAR images of oceanic eddies. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Techniques and Applications)
Figures

Figure 1

Open AccessArticle Refocusing Moving Ship Targets in SAR Images Based on Fast Minimum Entropy Phase Compensation
Sensors 2019, 19(5), 1154; https://doi.org/10.3390/s19051154
Received: 15 January 2019 / Revised: 27 February 2019 / Accepted: 4 March 2019 / Published: 7 March 2019
PDF Full-text (7557 KB) | HTML Full-text | XML Full-text
Abstract
Moving ship targets appear blurred and defocused in synthetic aperture radar (SAR) images due to the translation motion during the coherent processing. Motion compensation is required for refocusing moving ship targets in SAR scenes. A novel refocusing method for moving ship is developed [...] Read more.
Moving ship targets appear blurred and defocused in synthetic aperture radar (SAR) images due to the translation motion during the coherent processing. Motion compensation is required for refocusing moving ship targets in SAR scenes. A novel refocusing method for moving ship is developed in this paper. The method is exploiting inverse synthetic aperture radar (ISAR) technique to refocus the ship target in SAR image. Generally, most cases of refocusing are for raw echo data, not for SAR image. Taking into account the advantages of processing in SAR image, the processing data are SAR image rather than raw echo data in this paper. The ISAR processing is based on fast minimum entropy phase compensation method, an iterative approach to obtain the phase error. The proposed method has been tested using Spaceborne TerraSAR-X, Gaofeng-3 images and airborne SAR images of maritime targets. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Techniques and Applications)
Figures

Figure 1

Open AccessArticle Monitoring Land Subsidence in Wuhan City (China) using the SBAS-InSAR Method with Radarsat-2 Imagery Data
Sensors 2019, 19(3), 743; https://doi.org/10.3390/s19030743
Received: 21 December 2018 / Revised: 2 February 2019 / Accepted: 5 February 2019 / Published: 12 February 2019
PDF Full-text (7412 KB) | HTML Full-text | XML Full-text
Abstract
Wuhan city is the biggest city in central China and has suffered subsidence problems in recent years because of its rapid urban construction. However, longtime and wide range monitoring of land subsidence is lacking. The causes of subsidence also require further study, such [...] Read more.
Wuhan city is the biggest city in central China and has suffered subsidence problems in recent years because of its rapid urban construction. However, longtime and wide range monitoring of land subsidence is lacking. The causes of subsidence also require further study, such as natural conditions and human activities. We use small baseline subset (SBAS) interferometric synthetic aperture radar (InSAR) method and high-resolution RADARSAT-2 images acquired between 2015 and 2018 to derive subsidence. The SBAS-InSAR results are validated by 56 leveling benchmarks where two readings of elevation were recorded. Two natural factors (carbonate rock and soft soils) and three human factors (groundwater exploitation, subway excavation and urban construction) are investigated for their relationships with land subsidence. Results show that four major areas of subsidence are detected and the subsidence rate varies from −51.56 to 27.80 millimeters per year (mm/yr) with an average of −0.03 mm/yr. More than 83.81% of persistent scattered (PS) points obtain a standard deviation of less than −6 mm/yr, and the difference between SBAS-InSAR method and leveling data is less than 5 mm/yr. Thus, we conclude that SBAS-InSAR method with Radarsat-2 data is reliable for longtime monitoring of land subsidence covering a large area in Wuhan city. In addition, land subsidence is caused by a combination of natural conditions and human activities. Natural conditions provide a basis for subsidence and make subsidence possible. Human activities are driving factors and make subsidence happen. Moreover, subsidence information could be used in disaster prevention, urban planning, and hydrological modeling. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Techniques and Applications)
Figures

Figure 1

Open AccessArticle Improving the Topside Profile of Ionosonde with TEC Retrieved from Spaceborne Polarimetric SAR
Sensors 2019, 19(3), 516; https://doi.org/10.3390/s19030516
Received: 14 December 2018 / Revised: 23 January 2019 / Accepted: 23 January 2019 / Published: 26 January 2019
PDF Full-text (6685 KB) | HTML Full-text | XML Full-text
Abstract
Signals from spaceborne polarimetric synthetic aperture radar will suffer from Faraday rotations when they propagate through the ionosphere, especially those at L-band or lower frequencies, such as signals from the Phased Array type L-band Synthetic Aperture Radar (PALSAR). For this reason, Faraday rotation [...] Read more.
Signals from spaceborne polarimetric synthetic aperture radar will suffer from Faraday rotations when they propagate through the ionosphere, especially those at L-band or lower frequencies, such as signals from the Phased Array type L-band Synthetic Aperture Radar (PALSAR). For this reason, Faraday rotation compensation should be considered. On the other hand, Faraday rotation could also be retrieved from distorted echoes. Moreover, combining Faraday rotation with the radar parameters and the model of magnetic field, we could derive the total electron content (TEC) along the signal path. Benefiting from the high spatial resolution of the SAR system, TEC obtained from PALSAR could be orders of magnitude higher in spatial resolution than that from GPS. Besides, we demonstrated that the precision of TEC from PALSAR is also much higher than that from GPS. With the precise TEC available, we could fuse it with data from other ionosphere detection devices to improve their performances. In this paper, we adopted it to help modify the empirically modeled topside profile of ionosonde. The results show that the divergence between the modified profile and the referenced incoherent scattering radar profile reduced by about 30 percent when compared to the original ionosonde topside profile. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Techniques and Applications)
Figures

Figure 1

Open AccessArticle Accurate Wide Angle SAR Imaging Based on LS-CS-Residual
Sensors 2019, 19(3), 490; https://doi.org/10.3390/s19030490
Received: 4 December 2018 / Revised: 19 January 2019 / Accepted: 22 January 2019 / Published: 25 January 2019
PDF Full-text (1337 KB) | HTML Full-text | XML Full-text
Abstract
Wide angle synthetic aperture radar (WASAR) receives data from a large angle, which causes the problem of aspect dependent scattering. L1 regularization is a common compressed sensing (CS) model. The L1 regularization based WASAR imaging method divides the whole aperture into [...] Read more.
Wide angle synthetic aperture radar (WASAR) receives data from a large angle, which causes the problem of aspect dependent scattering. L 1 regularization is a common compressed sensing (CS) model. The L 1 regularization based WASAR imaging method divides the whole aperture into subapertures and reconstructs the subaperture images individually. However, the aspect dependent scattering recovery of it is not accurate. The subaperture images of WASAR can be regarded as the SAR video. The support set among the different frames of SAR video are highly overlapped. Least squares on compressed sensing residuals (LS-CS-Residuals) can reconstruct the time sequences of sparse signals which change slowly with time. This is to replace CS on the observation by CS on the least squares (LS) residual computed using the prior estimate of the support. In this paper, we introduce LS-CS-Residual into WASAR imaging. In the iteration of LS-CS-Residual, the azimuth-range decoupled operators are used to avoid the huge memory cost. Real data processing results show that LS-CS-Residual can estimate the aspect dependent scatterings of the targets more accurately than CS based methods. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Techniques and Applications)
Figures

Figure 1

Open AccessArticle Aspect Entropy Extraction Using Circular SAR Data and Scattering Anisotropy Analysis
Sensors 2019, 19(2), 346; https://doi.org/10.3390/s19020346
Received: 27 November 2018 / Revised: 13 January 2019 / Accepted: 15 January 2019 / Published: 16 January 2019
PDF Full-text (5582 KB) | HTML Full-text | XML Full-text
Abstract
In conventional synthetic aperture radar (SAR) working modes, targets are assumed isotropic because the viewing angle is small. However, most man-made targets are anisotropic. Therefore, anisotropy should be considered when the viewing angle is large. From another perspective, anisotropy is also a useful [...] Read more.
In conventional synthetic aperture radar (SAR) working modes, targets are assumed isotropic because the viewing angle is small. However, most man-made targets are anisotropic. Therefore, anisotropy should be considered when the viewing angle is large. From another perspective, anisotropy is also a useful feature. Circular SAR (CSAR) can detect the scattering variation under different azimuthal look angles by a 360-degree observation. Different targets usually have varying degrees of anisotropy, which aids in target discrimination. However, there is no effective method to quantify the degree of anisotropy. In this paper, aspect entropy is presented as a descriptor of the scattering anisotropy. The range of aspect entropy is from 0 to 1, which corresponds to anisotropic to isotropic. First, the method proposed extracts aspect entropy at the pixel level. Since the aspect entropy of pixels can discriminate isotropic and anisotropic scattering, the method prescreens the target from the isotropic clutters. Next, the method extracts aspect entropy at the target level. The aspect entropy of targets can discriminate between different types of targets. Then, the effect of noise on aspect entropy extraction is analyzed and a denoising method is proposed. The Gotcha public release dataset, an X-band circular SAR data, is used to validate the method and the discrimination capability of aspect entropy. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Techniques and Applications)
Figures

Figure 1

Open AccessCommunication SPARX, a MIMO Array for Ground-Based Radar Interferometry
Sensors 2019, 19(2), 252; https://doi.org/10.3390/s19020252
Received: 13 November 2018 / Revised: 2 January 2019 / Accepted: 5 January 2019 / Published: 10 January 2019
PDF Full-text (4405 KB) | HTML Full-text | XML Full-text
Abstract
Ground-Based SAR Interferometry (GB-InSAR) is nowadays a proven technique widely used for slope monitoring in open pit mines and landslide control. Traditional GB-InSAR techniques involve transmitting and receiving antennas moving on a scanner to achieve the desired synthetic aperture. Mechanical movement limits the [...] Read more.
Ground-Based SAR Interferometry (GB-InSAR) is nowadays a proven technique widely used for slope monitoring in open pit mines and landslide control. Traditional GB-InSAR techniques involve transmitting and receiving antennas moving on a scanner to achieve the desired synthetic aperture. Mechanical movement limits the acquisition speed of the SAR image. There is a need for faster acquisition time as it plays an important role in correcting rapidly varying atmospheric effects. Also, a fast imaging radar can extend the applications to the measurement of vibrations of large structures. Furthermore, the mechanical assembly put constraints on the transportability and weight of the system. To overcome these limitations an electronically switched array would be preferable, which however faces enormous technological and cost difficulties associated to the large number of array elements needed. Imaging Multiple-Input Multiple Output (MIMO) radars can be used as a significant alternative to usual mechanical SAR and full array systems. This paper describes the ground-based X-band MIMO radar SPARX recently developed by IDS GeoRadar in order to overcome the limits of IDS GeoRadar’s well-established ground based interferometric SAR systems. The SPARX array consists of 16 transmit and 16 receive antennas, organized in independent sub-modules and geometrically arranged in order to synthesize an equally spaced virtual array of 256 elements. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Techniques and Applications)
Figures

Figure 1

Open AccessArticle Extended Multiple Aperture Mapdrift-Based Doppler Parameter Estimation and Compensation for Very-High-Squint Airborne SAR Imaging
Sensors 2019, 19(1), 213; https://doi.org/10.3390/s19010213
Received: 31 October 2018 / Revised: 3 January 2019 / Accepted: 3 January 2019 / Published: 8 January 2019
PDF Full-text (6554 KB) | HTML Full-text | XML Full-text
Abstract
Doppler parameter estimation and compensation (DPEC) is an important technique for airborne SAR imaging due to the unpredictable disturbance of real aircraft trajectory. Traditional DPEC methods can be only applied for broadside, small- or medium-squint geometries, as they at most consider the spatial [...] Read more.
Doppler parameter estimation and compensation (DPEC) is an important technique for airborne SAR imaging due to the unpredictable disturbance of real aircraft trajectory. Traditional DPEC methods can be only applied for broadside, small- or medium-squint geometries, as they at most consider the spatial variance of the second-order Doppler phase. To implement the DPEC in very-high-squint geometries, we propose an extended multiple aperture mapdrift (EMAM) method in this paper for better accuracy. This advantage is achieved by further estimating and compensating the spatial variation of the third-order Doppler phase, i.e., the derivative of the Doppler rate. The main procedures of the EMAM, including the steps of sub-view image generation, sliding-window-based cross-correlation, and image-offset-based Doppler parameter estimation, are derived in detail, followed by the analyses for the EMAM performance. The presented approach is evaluated by both computer simulations and real airborne data. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Techniques and Applications)
Figures

Figure 1

Open AccessArticle Ship Classification in High-Resolution SAR Images via Transfer Learning with Small Training Dataset
Sensors 2019, 19(1), 63; https://doi.org/10.3390/s19010063
Received: 19 November 2018 / Revised: 18 December 2018 / Accepted: 20 December 2018 / Published: 24 December 2018
PDF Full-text (6738 KB) | HTML Full-text | XML Full-text
Abstract
Synthetic aperture radar (SAR) as an all-weather method of the remote sensing, now it has been an important tool in oceanographic observations, object tracking, etc. Due to advances in neural networks (NN), researchers started to study SAR ship classification problems with deep learning [...] Read more.
Synthetic aperture radar (SAR) as an all-weather method of the remote sensing, now it has been an important tool in oceanographic observations, object tracking, etc. Due to advances in neural networks (NN), researchers started to study SAR ship classification problems with deep learning (DL) in recent years. However, the limited labeled SAR ship data become a bottleneck to train a neural network. In this paper, convolutional neural networks (CNNs) are applied to ship classification by using SAR images with the small datasets. To solve the problem of over-fitting which often appeared in training small dataset, we proposed a new method of data augmentation and combined it with transfer learning. Based on experiments and tests, the performance is evaluated. The results show that the types of the ships can be classified in high accuracies and reveal the effectiveness of our proposed method. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Techniques and Applications)
Figures

Figure 1

Open AccessArticle Joint Sparsity Constraint Interferometric ISAR Imaging for 3-D Geometry of Near-Field Targets with Sub-Apertures
Sensors 2018, 18(11), 3750; https://doi.org/10.3390/s18113750
Received: 9 October 2018 / Revised: 30 October 2018 / Accepted: 31 October 2018 / Published: 2 November 2018
PDF Full-text (12303 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes a new interferometric near-field 3-D imaging approach based on multi-channel joint sparse reconstruction to solve the problems of conventional methods, i.e., the irrespective correlation of different channels in single-channel independent imaging which may lead to deviated positions of scattering points, [...] Read more.
This paper proposes a new interferometric near-field 3-D imaging approach based on multi-channel joint sparse reconstruction to solve the problems of conventional methods, i.e., the irrespective correlation of different channels in single-channel independent imaging which may lead to deviated positions of scattering points, and the low accuracy of imaging azimuth angle for real anisotropic targets. Firstly, two full-apertures are divided into several sub-apertures by the same standard; secondly, the joint sparse metric function is constructed based on scattering characteristics of the target in multi-channel status, and the improved Orthogonal Matching Pursuit (OMP) method is used for imaging solving, so as to obtain high-precision 3-D image of each sub-aperture; thirdly, comprehensive sub-aperture processing is performed using all sub-aperture 3-D images to obtain the final 3-D images; finally, validity of the proposed approach is verified by using simulation electromagnetic data and data measured in the anechoic chamber. Experimental results show that, compared with traditional interferometric ISAR imaging approaches, the algorithm proposed in this paper is able to provide a higher accuracy in scattering center reconstruction, and can effectively maintain relative phase information of channels. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Techniques and Applications)
Figures

Figure 1

Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top