remotesensing-logo

Journal Browser

Journal Browser

Processing of Bi-static, Geo-Synchronous and Multi-Satellite SAR Constellation Data

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 23770

Special Issue Editors

The State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan 430079, China
Interests: SAR remote sensing; SAR interferometry; surface motion estimation; SAR in archaeology
Special Issues, Collections and Topics in MDPI journals
School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China
Interests: geosynchronous SAR; SAR signal processing
Special Issues, Collections and Topics in MDPI journals
Dipartimento di Elettronica, Informatica, Bioingegneria, DEIB, Politecnico di Milano (emeritus), Piazza Leonardo da Vinci 32, 20133 Milano, Italy
Interests: synthetic aperture radar; differential interferometry (DInSAR); tomography; digital signal processing

Special Issue Information

Dear Colleagues,

Synthetic aperture radar (SAR) remote sensing has undergone a tremendous development in recent years. Recently, the trend in sensor development is moving towards constellations of sensors, as well as bi-static missions and smaller companion satellites, to extend the existing missions toward bi-static capabilities. The tremendous success of the TanDEM mission can be seen as the spark lightning the growing interest in bi-static mission concepts. Additionally, geo-synchronous missions will offer unique temporal resolutions, and are also in an early development stage. With upcoming sensors, like TanDEM-L and LuTan-1, as well as other concepts, a deeper look into the recent developments in bi-static/multi-static SAR processing and applications is essential for the widespread usage of the expected data.

We would like to invite you to submit articles about your recent research, with respect to the following topics:

  • Bi-/multi-static SAR processing
  • Applications for bi-static SAR processing and DEM production
  • Geo-synchronous concept and processing
  • Bi-/multi-static and geosynchronous SAR missions
  • Mono-static pursuit data SAR processing and applications

Prof. Dr. Robert Wang
Prof. Dr. Timo Balz
Prof. Dr. Fabio Rocca
Prof. Dr. Cheng Hu
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

  • SAR
  • Bi-static SAR
  • Geo-synchronous SAR
  • SAR processing
  • DEM
  • Surface motion

Published Papers (8 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

22 pages, 13778 KiB  
Article
An Advanced Phase Synchronization Scheme Based on Coherent Integration and Waveform Diversity for Bistatic SAR
by Da Liang, Heng Zhang, Yonghua Cai, Kaiyu Liu and Ke Zhang
Remote Sens. 2021, 13(5), 981; https://doi.org/10.3390/rs13050981 - 05 Mar 2021
Cited by 10 | Viewed by 1964
Abstract
In the bistatic synthetic aperture radar (BiSAR) system, the deviation between two oscillators in different platforms will cause an additional modulation of BiSAR echoes. Therefore, phase synchronization is one of the key issues that must be addressed for the BiSAR system. The oscillator [...] Read more.
In the bistatic synthetic aperture radar (BiSAR) system, the deviation between two oscillators in different platforms will cause an additional modulation of BiSAR echoes. Therefore, phase synchronization is one of the key issues that must be addressed for the BiSAR system. The oscillator phase error model and the principle of phase synchronization are firstly described. The waveform diversity technology has been widely used in many fields, for example, the hearing aids device and the recognition of auditory input source in cocktail party problem. Inspired by this, an advanced phase synchronization scheme based on coherent integration and waveform diversity is proposed. The synchronization signal and radar signal are orthogonal signals which can be separated by using waveform diversity technique. After extracting the synchronization signal, the phase synchronization accuracy can be further improved by coherent integration. The transmission of synchronization signals between two synchronization antennas is analyzed, followed by the theoretical error analysis. Then, the processing of separating the echo signal and synchronization signal is described in detail. The simulation experiments are performed. The accuracy of phase synchronization can reach 1 degree, which verifies the effectiveness of the proposed synchronization scheme. Full article
Show Figures

Figure 1

26 pages, 10551 KiB  
Article
An Accurate GEO SAR Range Model for Ultralong Integration Time Based on mth-Order Taylor Expansion
by Binbin Zhou, Xiangyang Qi and Heng Zhang
Remote Sens. 2021, 13(2), 255; https://doi.org/10.3390/rs13020255 - 13 Jan 2021
Cited by 4 | Viewed by 2113
Abstract
As the Geosynchronous Earth Orbital Synthetic Aperture Radar (GEO SAR) allows a wide area viewing combined with a short revisit cycle, it is suitable for many applications that require high timeliness, such as natural disaster monitoring, weather supervision, and military reconnaissance. However, the [...] Read more.
As the Geosynchronous Earth Orbital Synthetic Aperture Radar (GEO SAR) allows a wide area viewing combined with a short revisit cycle, it is suitable for many applications that require high timeliness, such as natural disaster monitoring, weather supervision, and military reconnaissance. However, the ultralong integration time and the invalidation of “stop-and-go” assumption caused by the raise of orbital height also greatly increase the difficulty of signal processing. In this paper, a generalized method for calculating the accurate propagation distance between a GEO satellite and a target with ultralong integration time is proposed. This range model is mainly composed of an accurate pulse transmitting distance and an error compensation term for “stop-and-go” assumption failure. The transmitting distance is obtained by Taylor expansion, and the specific derivation process of the general formula of the mth-order expansion is given, in this paper. As for the compensation term, this is achieved by approximately calculating the pulse receiving distance based on twice Taylor expansion, the first expansion is for fast-time and the other is for slow-time. Finally, a series of simulation experiments were conducted to verify the effectiveness and superiority of this new range model for an ultralong integration time. Full article
Show Figures

Graphical abstract

24 pages, 4969 KiB  
Article
A Novel Ship Imaging Method with Multiple Sinusoidal Functions to Match Rotation Effects in Geosynchronous SAR
by Wei Xiong, Ying Zhang, Xichao Dong, Chang Cui, Zheng Liu and Minghui Xiong
Remote Sens. 2020, 12(14), 2249; https://doi.org/10.3390/rs12142249 - 14 Jul 2020
Cited by 6 | Viewed by 2197
Abstract
Geosynchronous Synthetic Aperture Radar (GEO SAR) has a very long Coherent Processing Interval (in the order of hundreds of seconds) compared with other SAR platforms. Thus, the current methods of rotation effect matching and ship imaging that operate within a relatively short Coherent [...] Read more.
Geosynchronous Synthetic Aperture Radar (GEO SAR) has a very long Coherent Processing Interval (in the order of hundreds of seconds) compared with other SAR platforms. Thus, the current methods of rotation effect matching and ship imaging that operate within a relatively short Coherent Processing Interval (in the order of seconds) are obviously not applicable. To address this problem, a novel ship imaging method with multiple sinusoidal functions matching for rotation effects is proposed for GEO SAR. Firstly, the influence of the rotational motion of a ship on the slant range is analyzed. It can be matched with the sum of multiple sinusoidal functions, and the signal model of a ship with rotational motion is given. Then, multiple sinusoidal functions for the matching-based ship imaging method are proposed, and their procedures are presented as follows: (1) The Generalized Keystone Transform and Generalized Dechirp Process (GKTGDP) is modified to compensate for the range migration and phase caused by the motion of GEO SAR. Then, the signal is focused at the frequencies of sinusoidal functions, and the frequencies can be matched. (2) From the matched frequencies, the other parameters of sinusoidal functions can be matched by parameter searching. (3) Based on the matched results, the Back Projection Algorithm (BPA) is used to take an image of the ship with rotational motion. Finally, the effectiveness of the proposed method is verified by numerical experiments. Full article
Show Figures

Figure 1

23 pages, 6365 KiB  
Article
Geosynchronous Spaceborne-Airborne Bistatic Moving Target Indication System: Performance Analysis and Configuration Design
by Xichao Dong, Chang Cui, Yuanhao Li and Cheng Hu
Remote Sens. 2020, 12(11), 1810; https://doi.org/10.3390/rs12111810 - 03 Jun 2020
Cited by 13 | Viewed by 2217
Abstract
Geosynchronous spaceborne-airborne bistatic synthetic aperture radar (GEO SA-BSAR), consisting of GEO transmitter and airborne receiver, has stable coverage for a long time and benefits moving target detection. However, the performance of GEO SA-BSAR moving target indication (MTI) system varies widely between bistatic configurations. [...] Read more.
Geosynchronous spaceborne-airborne bistatic synthetic aperture radar (GEO SA-BSAR), consisting of GEO transmitter and airborne receiver, has stable coverage for a long time and benefits moving target detection. However, the performance of GEO SA-BSAR moving target indication (MTI) system varies widely between bistatic configurations. The traditional configuration design for GEO SA-BSAR system only considers the imaging performance, which may cause the poor MTI performance. In this paper, we propose a bistatic configuration design method to jointly optimize the MTI and SAR imaging performance for GEO SA-BSAR MTI system. The relationship between the MTI performance and bistatic configuration parameters is derived analytically and analyzed based on the maximum output signal to clutter and noise ratio (SCNR) criterion. Then, the MTI performance and SAR imaging performance are jointly considered to model the configuration design problem as a multi-objective optimization problem under the constrained condition. Finally, the optimal configuration for GEO SA-BSAR MTI system is given. Full article
Show Figures

Figure 1

24 pages, 7580 KiB  
Article
Azimuth Multichannel Reconstruction for Moving Targets in Geosynchronous Spaceborne–Airborne Bistatic SAR
by Wei Xu, Zhengbin Wei, Pingping Huang, Weixian Tan, Bo Liu, Zhiqi Gao and Yifan Dong
Remote Sens. 2020, 12(11), 1703; https://doi.org/10.3390/rs12111703 - 26 May 2020
Cited by 9 | Viewed by 2732
Abstract
In a multichannel geosynchronous spaceborne–airborne bistatic synthetic aperture radar (GEO-SA-BiSAR) system, the airborne receiver can obtain high-resolution microwave images with good signal-to-noise ratios (SNRs) by passively receiving echoes from the desired area. Since the Doppler modulation and range history of a moving target [...] Read more.
In a multichannel geosynchronous spaceborne–airborne bistatic synthetic aperture radar (GEO-SA-BiSAR) system, the airborne receiver can obtain high-resolution microwave images with good signal-to-noise ratios (SNRs) by passively receiving echoes from the desired area. Since the Doppler modulation and range history of a moving target are obviously different from a stationary target, a signal geometry model for moving targets in multichannel GEO-SA-BiSAR is established in this paper. According to simulation results, the along track velocity introduces target defocusing in azimuth, and the slant range velocity mainly causes multiple false targets. To resolve these problems, a modified multichannel reconstruction method in azimuth channel GEO-SA-BiSAR is proposed according to the azimuth multichannel impulse response of the imaged moving target. Before azimuth multichannel raw data combination, both spatial-variant range cell migration correction (RCMC) and azimuth nonlinear chirp scaling (ANLCS) should be performed to reduce the influence of the range offset and lower the Doppler bandwidth of the whole raw data, respectively. Afterward, a novel azimuth multichannel reconstruction algorithm is carried out via the modified reconstruction matrix based on the estimated target velocity. The target slant range velocity estimation is implemented by introducing the signal intensity ratio (SIR). Compared with the conventional method for the stationary target to handle the raw data of the moving target, the false targets could be obviously suppressed by using the proposed approach. Imaging results on both simulated point and distributed scene targets validate the proposed multichannel reconstruction approach. Full article
Show Figures

Graphical abstract

18 pages, 4154 KiB  
Article
Flexible Hierarchical Gaussian Mixture Model for High-Resolution Remote Sensing Image Segmentation
by Xue Shi, Yu Li and Quanhua Zhao
Remote Sens. 2020, 12(7), 1219; https://doi.org/10.3390/rs12071219 - 09 Apr 2020
Cited by 13 | Viewed by 3589
Abstract
The Gaussian mixture model (GMM) plays an important role in image segmentation, but the difficulty of GMM for modeling asymmetric, heavy-tailed, or multimodal distributions of pixel intensities significantly limits its application. One effective way to improve the segmentation accuracy is to accurately model [...] Read more.
The Gaussian mixture model (GMM) plays an important role in image segmentation, but the difficulty of GMM for modeling asymmetric, heavy-tailed, or multimodal distributions of pixel intensities significantly limits its application. One effective way to improve the segmentation accuracy is to accurately model the statistical distributions of pixel intensities. In this study, an innovative high-resolution remote sensing image segmentation algorithm is proposed based on a flexible hierarchical GMM (HGMM). The components are first defined by the weighted sums of elements, in order to accurately model the complicated distributions of pixel intensities in object regions. The elements of components are defined by Gaussian distributions to model the distributions of pixel intensities in local regions of the object region. Following the Bayesian theorem, the segmentation model is then built by combining the HGMM and the prior distributions of parameters. Finally, a novel birth or death Markov chain Monte Carlo (BDMCMC) is designed to simulate the segmentation model, which can automatically determine the number of elements and flexibly model complex distributions of pixel intensities. Experiments were implemented on simulated and real high-resolution remote sensing images. The results show that the proposed algorithm is able to flexibly model the complicated distributions and accurately segment images. Full article
Show Figures

Graphical abstract

22 pages, 4385 KiB  
Article
Formation Design for Single-Pass GEO InSAR Considering Earth Rotation Based on Coordinate Rotational Transformation
by Zhiyang Chen, Xichao Dong, Yuanhao Li and Cheng Hu
Remote Sens. 2020, 12(3), 573; https://doi.org/10.3390/rs12030573 - 08 Feb 2020
Cited by 9 | Viewed by 3475
Abstract
The single-pass geosynchronous synthetic aperture radar interferometry (GEO InSAR) adopts the formation of a slave satellite accompanying the master satellite, which can reduce the temporal decorrelation caused by atmospheric disturbance and observation time gap between repeated tracks. Current formation design methods for spaceborne [...] Read more.
The single-pass geosynchronous synthetic aperture radar interferometry (GEO InSAR) adopts the formation of a slave satellite accompanying the master satellite, which can reduce the temporal decorrelation caused by atmospheric disturbance and observation time gap between repeated tracks. Current formation design methods for spaceborne SAR are based on the Relative Motion Equation (RME) in the Earth-Centered-Inertial (ECI) coordinate system (referred to as ECI-RME). Since the Earth rotation is not taken into account, the methods will lead to a significant error for the baseline calculation while applied to formation design for GEO InSAR. In this paper, a formation design method for single-pass GEO InSAR based on Coordinate Rotational Transformation (CRT) is proposed. Through CRT, the RME in Earth-Centered-Earth-Fixed (ECEF) coordinate system (referred to as ECEF-RME) is derived. The ECEF-RME can be used to describe the accurate baseline of close-flying satellites for different orbital altitudes, but not limited to geosynchronous orbit. Aiming at the problem that ECEF-RME does not have a regular geometry as ECI-RME does, a numerical formation design method based on the minimum baseline error criterion is proposed. Then, an analytical formation design method is proposed for GEO InSAR, based on the Minimum Along-track Baseline Criterion (MABC) subject to a fixed root mean square of the perpendicular baseline. Simulation results verify the validity of the ECEF-RME and the analytical formation design method. The simulation results also show that the proposed method can help alleviate the atmospheric phase impacts and improve the retrieval accuracy of the digital elevation model (DEM) compared with the ECI-RME-based approach. Full article
Show Figures

Graphical abstract

23 pages, 1337 KiB  
Article
Along-Track Multistatic Synthetic Aperture Radar Formations of Minisatellites
by Pietro Guccione, Andrea Monti Guarnieri, Fabio Rocca, Davide Giudici and Nico Gebert
Remote Sens. 2020, 12(1), 124; https://doi.org/10.3390/rs12010124 - 01 Jan 2020
Cited by 27 | Viewed by 4237
Abstract
The paper analyses an along-track multistatic Synthetic Aperture Radar (SAR) formation. The formation aims at achieving a high azimuth resolution maintaining at the same time a large swath width. The case with one transmitting sensor and all receiving is analyzed (Single Input Multiple [...] Read more.
The paper analyses an along-track multistatic Synthetic Aperture Radar (SAR) formation. The formation aims at achieving a high azimuth resolution maintaining at the same time a large swath width. The case with one transmitting sensor and all receiving is analyzed (Single Input Multiple Output, SIMO). An effective and novel reconstruction, in the two-dimensional frequency domain is introduced that is able to keep low the azimuth ambiguity and achieve a recombination gain close to the theoretical one. Degradation of the system performance due to the loss of the control of formation position is analyzed using probabilistic considerations. Moreover, some innovative methods to mitigate the loss of optimality are introduced and evaluated using simulations. Finally, considerations on the impact of the across-track non zero baseline are discussed. Full article
Show Figures

Graphical abstract

Back to TopTop