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Synthetic Aperture Radar (SAR) Simulation and Processing

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

Deadline for manuscript submissions: closed (31 May 2021) | Viewed by 25225

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Prof. Dr. Antonio Iodice

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Dipartimento di Ingegneria Elettrica e Tecnologie dell'Informazione, Università degli Studi di Napoli Federico II, Via Claudio 21, 80125 Napoli, Italy
Interests: electromagnetics; scattering; propagation; synthetic aperture radar; SAR
Special Issues, Collections and Topics in MDPI journals

Dr. Gerardo Di Martino

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Department of Electrical Engineering and Information Technology (DIETI), University of Naples Federico II, 80125 Napoli, Italy
Interests: electromagnetic propagation; electromagnetic modeling; microwave remote sensing and electromagnetics; SAR signal processing and simulation; information retrieval from SAR data
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Synthetic Aperture Radar (SAR) is a powerful remote sensing technique able to perform global and almost continuous monitoring of the Earth’s surface, thanks to its all-weather and day-and-night acquisition capabilities. It is now a well-established technology, and the main space agencies in the world have launched several SAR missions that currently provide us with an unprecedented amount of data. However, exctracting from such data the information required by each of the many potential applications (soil moisture retrieval, urban area monitoring, sea state monitoring, wind retrieval, ship detection, etc.) is often not an easy task. It requires on one hand refined data processing, and, on the other hand, proper models to simulate the interaction between the observed scene and the impinging electromagnetic wave. In addition, new missions implementing new acquisition modes (e.g., TOPS, forward-looking, staggered SAR) and observation geometries (bistatic, multistatic) are currently being planned. Therefore, new processing methods must be devised, and SAR raw signal simulation techniques must be developed to help engineers design new SAR systems.

Within this framework, for this Special Issue contributions are solicited on the following topics:

- SAR raw signal simulation techniques;

- simulation of bistatic and/or multistatic SAR systems;

- electromagnetic scattering models for SAR signal simulation;

- innovative SAR processing algorithms;

- SAR processing algorithms for innovative acquisition modes and geometries;

- post-processing techniques;

- SAR despeckling;

- Interferometric and polarimentric SAR processing methods;

- SAR tomography; and

- observed surface parameters retrieval.

Prof. Dr. Antonio Iodice
Dr. Gerardo Di Martino
Guest Editors

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Keywords

synthetic aperture radar (SAR) image processing;
SAR signal modeling and simulation;
new SAR sensors/concepts;
new SAR acquisition modes;
SAR polarimetry;
across/along track SAR interferometry;
SAR tomography;
electromagnetic scattering;
surface parameters retrieval.

Published Papers (11 papers)

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Research

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20 pages, 13042 KiB

Open AccessArticle

Spiral SAR Imaging with Fast Factorized Back-Projection: A Phase Error Analysis

by Juliana A. Góes, Valquiria Castro, Leonardo Sant’Anna Bins and Hugo E. Hernandez-Figueroa

Sensors 2021, 21(15), 5099; https://doi.org/10.3390/s21155099 - 28 Jul 2021

Cited by 10 | Viewed by 2325

Abstract

This paper presents a fast factorized back-projection (FFBP) algorithm that can satisfactorily process real P-band synthetic aperture radar (SAR) data collected from a spiral flight pattern performed by a drone-borne SAR system. Choosing the best setup when processing SAR data with an FFBP algorithm is not so straightforward, so predicting how this choice will affect the quality of the output image is valuable information. This paper provides a statistical phase error analysis to validate the hypothesis that the phase error standard deviation can be predicted by geometric parameters specified at the start of processing. In particular, for a phase error standard deviation of ~12°, the FFBP is up to 21 times faster than the direct back-projection algorithm for 3D images and up to 13 times faster for 2D images. Full article

(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Simulation and Processing)

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17 pages, 3010 KiB

Open AccessArticle

Time-Domain and Monostatic-like Frequency-Domain Methods for Bistatic SAR Simulation

by Gerardo Di Martino, Antonio Iodice, Antonio Natale and Daniele Riccio

Sensors 2021, 21(15), 5012; https://doi.org/10.3390/s21155012 - 23 Jul 2021

Cited by 5 | Viewed by 1665

Abstract

In recent years, an increasing interest has been devoted to bistatic SAR configurations, which can be effectively used to improve system performance and/or to increase the amount of physical information retrievable from the observed scene. Within this context, the availability of simulation tools is of paramount importance, for both mission planning and processing algorithm verification and testing. In this paper, a time domain simulator useful to obtain the point-spread function and the raw signal for the generic bistatic SAR configuration is presented. Moreover, we focus on the case of two bistatic configurations, which are of considerable interest in actual SAR applications, i.e., the translational invariant SAR and the one-stationary SAR acquisition geometries, for which we obtain meaningful expressions of the Transfer Functions. In particular, these expressions are formally equal to those obtained for the monostatic SAR configuration, so that the already available monostatic simulator can be easily adapted to these bistatic cases. The point-target raw signals obtained using the (exact) time domain simulator and the (approximated) frequency domain one are compared, with special attention to acquisition geometries that may be of practical interest in Formation-Flying SAR applications. Results show that the phase difference between raw signals simulated with the two approaches is, in all cases, smaller (and often much smaller) than about 10 degrees, except that at the very edge of the raw signals, where however, it does not exceed about 50 degrees. Full article

(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Simulation and Processing)

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32 pages, 9435 KiB

Open AccessArticle

Novel Weight-Based Approach for Soil Moisture Content Estimation via Synthetic Aperture Radar, Multispectral and Thermal Infrared Data Fusion

by Oualid Yahia, Raffaella Guida and Pasquale Iervolino

Sensors 2021, 21(10), 3457; https://doi.org/10.3390/s21103457 - 15 May 2021

Cited by 7 | Viewed by 2129

Abstract

Though current remote sensing technologies, especially synthetic aperture radars (SARs), exhibit huge potential for soil moisture content (SMC) retrievals, such technologies also present several performance disadvantages. This study explored the merits of proposing a novel data fusion methodology (partly decision level and partly feature level) for SMC estimation. Initially, individual estimations were derived from three distinct methods: the inversion of an Empirically Adapted Integral Equation Model (EA-IEM) applied to SAR data, the Perpendicular Drought Index (PDI), and the Temperature Vegetation Dryness Index (TVDI) determined from Landsat-8 data. Subsequently, three feature level fusions were performed to produce three different novel salient feature combinations where said features were extracted from each of the previously mentioned methods to be the input of an artificial neural network (ANN). The latter underwent a modification of its performance function, more specifically from absolute error to root mean square error (RMSE). Eventually, all SMC estimations, including the feature level fusion estimation, were fused at the decision level through a novel weight-based estimation. The performance of the proposed system was analysed and validated by measurements collected from three study areas, an agricultural field in Blackwell farms, Guildford, United Kingdom, and two different agricultural fields in Sidi Rached, Tipasa, Algeria. Those measurements contained SMC levels and surface roughness profiles. The proposed SMC estimation system yielded stronger correlations and lower RMSE values than any of the considered SMC estimation methods in the order of 0.38%, 1.4%, and 1.09% for the Blackwell farms, Sidi Rached 1, and Sidi Rached 2 datasets, respectively. Full article

(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Simulation and Processing)

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24 pages, 35447 KiB

Open AccessArticle

Sea Spike Suppression Method Based on Optimum Polarization Ratio in Airborne SAR Images

by Yawei Zhao, Jinsong Chong, Yan Li, Kai Sun and Xue Yang

Sensors 2021, 21(9), 3269; https://doi.org/10.3390/s21093269 - 09 May 2021

Cited by 3 | Viewed by 1695

Abstract

In the condition of ocean observation for high-resolution airborne synthetic aperture radar (SAR), sea spikes will cause serious interference to SAR image interpretation and marine target detection. In order to improve the ability of target detection, it is necessary to suppress sea spikes in SAR images. However, there is no report on sea spike suppression methods in SAR images. As a step forward, a sea spike suppression method based on optimum polarization ratio in airborne SAR images is proposed in this paper. This method is only applicable to the situation where VV and HH dual-polarized SAR data containing sea spikes are acquired at the same time. By calculating the optimum polarization ratio, this method further obtains the difference image of the panoramic area accomplishing sea spike suppression. This method is applied to a field airborne X-band SAR data, including ocean waves, oil spills and ships. The results show that the sea spikes are well suppressed, the contrast of ocean waves and the contrast of oil spills are improved, and the false alarm rate of ship detection is reduced. The discussions on these results demonstrate that the proposed method can effectively suppress sea spikes and improve the interpretability of SAR images. Full article

(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Simulation and Processing)

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17 pages, 8510 KiB

Open AccessArticle

Feature Preserving Autofocus Algorithm for Phase Error Correction of SAR Images

by Haemin Lee, Chang-Sik Jung and Ki-Wan Kim

Sensors 2021, 21(7), 2370; https://doi.org/10.3390/s21072370 - 29 Mar 2021

Cited by 8 | Viewed by 2451

Abstract

Autofocus is an essential technique for airborne synthetic aperture radar (SAR) imaging to correct phase errors mainly due to unexpected motion error. There are several well-known conventional autofocus methods such as phase gradient autofocus (PGA) and minimum entropy (ME). Although these methods are still widely used for various SAR applications, each method has drawbacks such as limited bandwidth of estimation, low convergence rate, huge computation burden, etc. In this paper, feature preserving autofocus (FPA) algorithm is newly proposed. The algorithm is based on the minimization of the cost function containing a regularization term. The algorithm is designed for postprocessing purpose, which is different from the existing regularization-based algorithms such as sparsity-driven autofocus (SDA). This difference makes the proposed method far more straightforward and efficient than those existing algorithms. The experimental results show that the proposed algorithm achieves better performance, convergence, and robustness than the existing postprocessing autofocus algorithms. Full article

(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Simulation and Processing)

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16 pages, 27633 KiB

Open AccessArticle

Extended GLRT Detection of Moving Targets for Multichannel SAR Based on Generalized Steering Vector

by Chong Song, Bingnan Wang, Maosheng Xiang and Wei Li

Sensors 2021, 21(4), 1478; https://doi.org/10.3390/s21041478 - 20 Feb 2021

Cited by 3 | Viewed by 2196

Abstract

A generalized likelihood ratio test (GLRT) with the constant false alarm rate (CFAR) property was recently developed for adaptive detection of moving targets in focusing synthetic aperture radar (SAR) images. However, in the multichannel SAR-ground moving-target indication (SAR-GMTI) system, image defocus is inevitable, which will remarkably degrade the performance of the GLRT detector, especially for the lower radar cross-section (RCS) and slower radial velocity moving targets. To address this issue, based on the generalized steering vector (GSV), an extended GLRT detector is proposed and its performance is evaluated by the optimum likelihood ratio test (LRT) in the Neyman-Pearson (NP) criterion. The joint data vector formulated by the current cell and its adjacent cells is used to obtain the GSV, and then the extended GLRT is derived, which coherently integrates signal and accomplishes moving-target detection and parameter estimation. Theoretical analysis and simulated SAR data demonstrate the effectiveness and robustness of the proposed detector in the defocusing SAR images. Full article

(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Simulation and Processing)

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19 pages, 17038 KiB

Open AccessArticle

A Coherence Improvement Method Based on Sub-Aperture InSAR for Human Activity Detection

by Zhongbin Wang, Bingnan Wang, Maosheng Xiang, Xiaoning Hu, Chong Song, Shuai Wang and Yachao Wang

Sensors 2021, 21(4), 1424; https://doi.org/10.3390/s21041424 - 18 Feb 2021

Cited by 2 | Viewed by 1880

Abstract

Human activity detection plays an important role in social security monitoring. Since human activity is very weak, it is necessary to employ the repeat-pass Interferometric Synthetic Aperture Radar (InSAR) technique to detect the potential activity between two data acquisitions; a high level of coherence is required for detection. With the object of detecting human activity of interest, this paper presents a coherence improvement approach based on sub-aperture InSAR for human activity detection. Different sub-apertures contain different scattering information of the target, as they represent the backscatter of the target from a different range of angles. Integrating corresponding sub-aperture interferometric results can improve the coherence between two complex images compared to the entire synthetic aperture, as well as removing a little disturbance in some circumstances. To validate the method presented in this paper, the actual airborne Ka-band frequency modulated continuous wave (FMCW) InSAR data acquired by the Aerospace Information Research Institute, Chinese Academy of Sciences (AIRCAS) are utilized. The experimental results demonstrate that the proposed method can effectively improve the coherence between two complex SAR images and can validly detect human activity of interest. Full article

(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Simulation and Processing)

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23 pages, 9025 KiB

Open AccessArticle

A Novel MIMO-SAR System Based on Simultaneous Digital Beam Forming of Both Transceiver and Receiver

by Yuzhen Zhao, Longyong Chen, Fubo Zhang, Yanlei Li and Yirong Wu

Sensors 2020, 20(22), 6604; https://doi.org/10.3390/s20226604 - 18 Nov 2020

Cited by 3 | Viewed by 2076

Abstract

Orthogonal frequency division multiplexing (OFDM) chirp waveform, which is composed of two or more successive identical linear frequency modulated sub pulses, is a newly proposed orthogonal waveform scheme for multi-input multi-output (MIMO) synthetic aperture radar (SAR) systems. However, according to the waveform model, there will be range ambiguity if the mapping width exceeds the maximum unambiguous width determined by the transmitted signal. This greatly limits its application in high-resolution wide-swath (HRWS) remote sensing. The traditional system divides the echoes by digital beam forming (DBF) to solve this problem, but the energy utilization rate is low. A MIMO-SAR system using simultaneous digital beam forming of both transceiver and receiver to avoid range ambiguity is designed in this paper. Compared with traditional system, the novel system designed in this paper obtain higher energy utilization and waveform orthogonality. Full article

(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Simulation and Processing)

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19 pages, 4565 KiB

Open AccessArticle

Research on Turning Motion Targets and Velocity Estimation in High Resolution Spaceborne SAR

by Xuejiao Wen and Xiaolan Qiu

Sensors 2020, 20(8), 2201; https://doi.org/10.3390/s20082201 - 13 Apr 2020

Cited by 8 | Viewed by 2317

Abstract

The development of high resolution SAR makes the influence of moving target more prominent, which results in defocusing and other unexplained phenomena. This paper focuses on the research of imaging signatures and velocity estimation of turning motion targets. In this paper, the turning motion is regarded as the straight line motion of continuous change of moving direction. Through the analysis of the straight line motion with constant velocity and the geometric modeling of the turning motion in spaceborne SAR, the imaging signatures of the turning motion target are obtained, such as the broken line phenomenon at the curve. Furthermore, a method for estimating the turning velocity is proposed here. The radial velocity is calculated by the azimuth offset of the turning motion target and the azimuth velocity is calculated by the phase error compensated in the refocusing process. The amplitude and direction of the velocity can be obtained by using both of them. The results of simulation and GF-3 data prove the accuracy of the analysis of turning motion imaging signatures, and they also show the accuracy and validity of the velocity estimation method in this paper. Full article

(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Simulation and Processing)

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13 pages, 2043 KiB

Open AccessArticle

Optimization of Weighting Window Functions for SAR Imaging via QCQP Approach

by Jin Liu, Wei Wang and Hongjun Song

Sensors 2020, 20(2), 419; https://doi.org/10.3390/s20020419 - 11 Jan 2020

Cited by 8 | Viewed by 2957

Abstract

Weighting window functions are commonly used in Synthetic Aperture Radar (SAR) imaging to suppress the high Peak SideLobe Ratio (PSLR) at the price of probable Signal-to-Noise Ratio (SNR) loss and mainlobe widening. In this paper, based on the method of designing a mismatched filter, we have proposed a Quadratically Constrained Quadratic Program (QCQP) approach, which is a convex that can be solved efficiently, to optimize the weighting window function with both amplitude and phase, expecting to offer better imaging performance, especially on PSLR, SNR loss, and mainlobe width. According to this approach and its modified form, we are able to design window functions to optimize the PSLR or the SNR loss under different kinds of flexible and practical constraints. Compared to the ordinary real-valued and symmetric window functions, like the Taylor window, the designed window functions are complex-valued and can be asymmetric. By using Synthetic Aperture Radar (SAR) point target imaging simulation, we show that the optimized weighting window function can clearly show the weak target hidden in the sidelobes of the strong target. Full article

(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Simulation and Processing)

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Review

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40 pages, 10955 KiB

Open AccessReview

Ground Moving Target Imaging via SDAP-ISAR Processing: Review and New Trends

by Marco Martorella, Samuele Gelli and Alessio Bacci

Sensors 2021, 21(7), 2391; https://doi.org/10.3390/s21072391 - 30 Mar 2021

Cited by 5 | Viewed by 2326

Abstract

Ground moving target imaging finds its main applications in both military and homeland security applications, with examples in operations of intelligence, surveillance and reconnaissance (ISR) as well as border surveillance. When such an operation is performed from the air looking down towards the ground, the clutter return may be comparable or even stronger than the target’s, making the latter hard to be detected and imaged. In order to solve this problem, multichannel radar systems are used that are able to remove the ground clutter and effectively detect and image moving targets. In this feature paper, the latest findings in the area of Ground Moving Target Imaging are revisited that see the joint application of Space-Time Adaptive Processing and Inverse Synthetic Aperture Radar Imaging. The theoretical aspects analysed in this paper are supported by practical evidence and followed by application-oriented discussions. Full article

(This article belongs to the Special Issue Synthetic Aperture Radar (SAR) Simulation and Processing)

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