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High Earth Orbit Spaceborne SAR Systems, Technologies, and Applications

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

Deadline for manuscript submissions: closed (15 April 2025) | Viewed by 7716

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Dr. Jianlai Chen

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Guest Editor

School of Aeronautics and Astronautics, Central South University, Changsha 410083, China
Interests: synthetic aperture radar (SAR) imaging; radar image recognition and interpretation
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Dr. Yongkang Li

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Guest Editor

School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, China
Interests: Synthetic aperture radar (SAR) imaging; geosynchronous SAR; SAR ground moving target indication (GMTI)

Dr. Yu Li

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Guest Editor

National Key Laboratory of Science and Technology on Space Microwave, Xi’an Institute of Space Radio Technology, Xi’an 710000, China
Interests: artificial intelligence; sensing-communication technique; airborne moving target indication (AMTI)
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Prof. Dr. Mengdao Xing

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Guest Editor

National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China
Interests: synthetic aperture radar (SAR); inverse SAR; sparse signal processing
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Special Issue Information

Dear Colleagues,

During the past two decades, many countries have attached great importance to high Earth orbit spaceborne SAR systems, technologies, and applications. In particular, China has successfully launched the world’s first geosynchronous Earth orbit SAR in August 2023. It is generally believed that the high Earth orbit spaceborne SAR is an important development direction in the future, because of its advantages of large coverage, short revisit time, and strong anti-destruction ability. However, compared with the conventional low orbit spaceborne SAR, the research on the high Earth orbit spaceborne SAR is not yet sufficient. Therefore, this Special Issue aims to invite scholars to publish articles on the latest progress on high Earth orbit spaceborne SAR systems, technologies, and applications.

The focus of this Special Issue is to report the latest progress on high Earth orbit spaceborne SAR systems, technologies, and applications. Specifically, it includes (but is not limited to) the research of advanced radar technology, the latest high Earth orbit spaceborne SAR imaging theory, and the latest moving target indication methods for high Earth orbit spaceborne SAR.

Potential topics for this Topic include, but are not limited to, the following:

Novel high Earth orbit spaceborne SAR missions, systems, and techniques.
Imaging methods for high Earth orbit spaceborne SAR;
Artificial intelligence in high Earth orbit spaceborne SAR applications;
Moving target indication methods for high Earth orbit spaceborne SAR;
On-board real-time processing of high Earth orbit spaceborne SAR images;
Image recognition and interpretation methods for high Earth orbit spaceborne SAR;
Integrated satellite-ground/air dual-functional sensing-communication technique;
Other related topics.

Dr. Jianlai Chen
Dr. Yongkang Li
Dr. Yu Li
Prof. Dr. Mengdao Xing
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

new imaging mechanism and theory
high earth orbit spaceborne sar
moving target indication
SAR image recognition and interpretation
artificial intelligence in SAR applications

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Published Papers (6 papers)

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Research

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20 pages, 2917 KiB

Open AccessArticle

Robust Beamforming for Frequency Diverse Array Multiple-Input Multiple-Output Radar: Mitigating Steering Vector Mismatches and Suppressing Main Lobe Interference

by Yumei Tan, Yong Li, Wei Cheng, Limeng Dong, Langhuan Geng and Muhammad Moin Akhtar

Remote Sens. 2025, 17(4), 577; https://doi.org/10.3390/rs17040577 - 8 Feb 2025

Viewed by 524

Abstract

Frequency Diverse Array Multiple-Input Multiple-Output (FDA-MIMO) radar introduces range-dependent beamforming capabilities, enhancing its ability to differentiate true targets from main lobe jammers. However, this innovation also introduces new challenges, particularly when errors disrupt the transceiver steering vectors, leading to performance degradation in main lobe interference suppression. To this end, a robust beamforming method tailored for FDA-MIMO radar systems is proposed to address signal mismatches caused by range–angle errors, array element position errors, frequency offsets, and coherent local scattering. Initially, a logarithmic function is used to decouple range and angle, enabling the design of a stable beampattern. The desired steering vector is then computed by addressing an optimization problem that leverages the interference-plus-noise covariance matrix alongside the signal-plus-noise covariance matrix. This estimation process, combined with mismatch correction through the diagonal loading method, significantly stabilizes the covariance matrix and enhances the robustness of FDA-MIMO systems. Extensive simulations validate the proposed approach across various error scenarios specific to FDA-MIMO radars, demonstrating superior robustness in main lobe interference suppression. These findings contribute to advancing robust beamforming techniques for FDA-MIMO radar systems, paving the way for enhanced performance in complex and error-prone environments. Full article

(This article belongs to the Special Issue High Earth Orbit Spaceborne SAR Systems, Technologies, and Applications)

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21 pages, 6412 KiB

Open AccessArticle

Detection of Flight Target via Multistatic Radar Based on Geosynchronous Orbit Satellite Irradiation

by Jia Dong, Peng Liu, Bingnan Wang and Yaqiu Jin

Remote Sens. 2024, 16(23), 4582; https://doi.org/10.3390/rs16234582 - 6 Dec 2024

Viewed by 860

Abstract

As a special microwave detection system, multistatic radar has obvious advantages in covert operation, anti-jamming, and anti-stealth due to its configuration of spatial diversity. As a high-orbit irradiation source, a geosynchronous orbit satellite (GEO) has the advantages of a low revisit period, large beam coverage area, and stable power of ground beam compared with traditional passive radar irradiation sources. This paper focuses on the key technologies of flight target detection in multistatic radar based on geosynchronous orbit satellite irradiation with one transmitter and multiple receivers. We carry out the following work: Firstly, we aim to address the problems of low signal-to-noise ratio (SNR) and range cell migration of high-speed cruise targets. The Radon–Fourier transform constant false alarm rate detector-range cell migration correction (RFT-CFAR-RCMC) is adopted to realize the coherent integration of echoes with range cell migration correction (RCM) and Doppler phase compensation. It significantly improves the SNR. Furthermore, we utilize the staggered PRF to solve the ambiguity and obtain multi-view data. Secondly, based on the aforementioned target multi-view detection data, the linear least square (LLS) multistatic positioning method combining bistatic range positioning (BR) and time difference of arrival positioning (TDOA) is used, which constructs the BR and TDOA measurement equations and linearizes by mathematical transformation. The measurement equations are solved by the LLS method, and the target positioning and velocity inversion are realized by the fusion of multistatic data. Finally, using target positioning data as observation values of radar, the Kalman filter (KF) is used to achieve flight trajectory tracking. Numerical simulation verifies the effectiveness of the proposed process. Full article

(This article belongs to the Special Issue High Earth Orbit Spaceborne SAR Systems, Technologies, and Applications)

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18 pages, 2075 KiB

Open AccessArticle

Multiple-Input Multiple-Output Synthetic Aperture Radar Waveform and Filter Design in the Presence of Uncertain Interference Environment

by Ke Xu, Guohao Sun, Yuandong Ji, Zhiquan Ding and Wenhao Chen

Remote Sens. 2024, 16(23), 4413; https://doi.org/10.3390/rs16234413 - 25 Nov 2024

Viewed by 863

Abstract

Multiple-input multiple-output synthetic aperture radar (MIMO-SAR) anti-jamming waveform design relies on accurate prior information about the interference. However, it is difficult to obtain accurate prior knowledge about uncertain intermittent sampling repeater jamming (ISRJ), leading to a severe decline in the detection performance of MIMO-SAR systems. Therefore, this article studies the robust joint design problem of MIMO radar transmit waveform and filter against uncertain ISRJ. We characterize two categories of uncertain interference, including sample length uncertainty and sample-time uncertainty, modeled as Gaussian distribution in different range bins. Based on the uncertain interference model, we formulate the maximizing SINR as a figure of merit, which is a non-convex quadratic optimization problem under specific waveform constraints. Based on the alternating direction method of multipliers (ADMM) framework, a novel joint design algorithm of waveform and filter is proposed. In order to improve the convergence performance of ADMM, the difference in convex functions (DC) programming is applied to the ADMM iterations framework to solve the problem of waveform energy inequality constraint. Finally, numerical results demonstrate the effectiveness and robustness of the proposed method, compared to the existing methods that utilize deterministic interference models in the uncertain ISRJ environment. Moreover, the spaceborne SAR real scene imaging simulations are conducted to evaluate the anti-ISRJ performance. Full article

(This article belongs to the Special Issue High Earth Orbit Spaceborne SAR Systems, Technologies, and Applications)

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16 pages, 4191 KiB

Open AccessCommunication

Optical-to-SAR Translation Based on CDA-GAN for High-Quality Training Sample Generation for Ship Detection in SAR Amplitude Images

by Baolong Wu, Haonan Wang, Cunle Zhang and Jianlai Chen

Remote Sens. 2024, 16(16), 3001; https://doi.org/10.3390/rs16163001 - 15 Aug 2024

Cited by 1 | Viewed by 1473

Abstract

Abundant datasets are critical to train models based on deep learning technologies for ship detection applications. Compared with optical images, ship detection based on synthetic aperture radar (SAR) (especially the high-Earth-orbit spaceborne SAR launched recently) lacks enough training samples. A novel cross-domain attention GAN (CDA-GAN) model is proposed for optical-to-SAR translation, which can generate high-quality SAR amplitude training samples of a target by optical image conversion. This high quality includes high geometry structure similarity of the target compared with the corresponding optical image and low background noise around the target. In the proposed model, the cross-domain attention mechanism and cross-domain multi-scale feature fusion are designed to improve the quality of samples for detection based on the generative adversarial network (GAN). Specifically, a cross-domain attention mechanism is designed to simultaneously emphasize discriminative features from optical images and SAR images at the same time. Moreover, a designed cross-domain multi-scale feature fusion module further emphasizes the geometric information and semantic information of the target in a feature graph from the perspective of global features. Finally, a reference loss is introduced in CDA-GAN to completely retain the extra features generated by the cross-domain attention mechanism and cross-domain multi-scale feature fusion module. Experimental results demonstrate that the training samples generated by the proposed CDA-GAN can obtain higher ship detection accuracy using real SAR data than the other state-of-the-art methods. The proposed method is generally available for different orbit SARs and can be extended to the high-Earth-orbit spaceborne SAR case. Full article

(This article belongs to the Special Issue High Earth Orbit Spaceborne SAR Systems, Technologies, and Applications)

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23 pages, 8720 KiB

Open AccessArticle

Mitigation of Suppressive Interference in AMPC SAR Based on Digital Beamforming

by Zhipeng Xiao, Feng He, Zaoyu Sun and Zehua Zhang

Remote Sens. 2024, 16(15), 2812; https://doi.org/10.3390/rs16152812 - 31 Jul 2024

Viewed by 1084

Abstract

Multichannel Synthetic Aperture Radar (MC-SAR) systems, such as Azimuth Multi-Phase Centre (AMPC) SAR, provide an effective solution for achieving high-resolution wide-swath (HRWS) imaging by reducing the pulse repetition frequency (PRF) to increase the swath width. However, in an Electronic Countermeasures (ECM) environment, the image quality of multichannel SAR systems can be significantly degraded by electromagnetic interference. Previous research into interference and counter-interference techniques has predominantly focused on single-channel SAR systems, with relatively few studies addressing the specific challenges faced by MC-SAR systems. This paper uses the classical spatial filtering technique of adaptive digital beamforming (DBF). Considering the Doppler ambiguity present in the echoes, two schemes—Interference Reconstruction And Cancellation (IRC) and Channel Grouping Nulling (CGN)—are designed to effectively eliminate suppressive interference. The IRC method eliminates the effects of interference without losing spatial degrees of freedom, ensuring effective suppression of Doppler ambiguity in subsequent processing. This method shows significant advantages under conditions of strong Doppler ambiguity and low jammer-to-signal ratio. Conversely, the CGN method mitigates the effect of interference on multichannel imaging at the expense of degrees of freedom redundant to Doppler ambiguity suppression. It shows remarkable interference suppression performance under weak-Doppler-ambiguity conditions, allowing for better image recovery. Simulations performed on point and distributed targets have validated that the proposed methods can effectively remove interfering signals and achieve high-resolution wide-swath (HRWS) SAR images. Full article

(This article belongs to the Special Issue High Earth Orbit Spaceborne SAR Systems, Technologies, and Applications)

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17 pages, 3387 KiB

Open AccessTechnical Note

High-Resolution SAR-to-Multispectral Image Translation Based on S2MS-GAN

by Yang Liu, Qingcen Han, Hong Yang and Huizhu Hu

Remote Sens. 2024, 16(21), 4045; https://doi.org/10.3390/rs16214045 - 30 Oct 2024

Viewed by 1286

Abstract

Synthetic aperture radar (SAR) has been extensively applied in remote sensing applications. Nevertheless, it is a challenge to process and interpret SAR images. The key to interpreting SAR images lies in transforming them into other forms of remote sensing images to extract valuable hidden remote sensing information. Currently, the conversion of SAR images to optical images produces low-quality results and incomplete spectral information. To address these problems, an end-to-end network model, S2MS-GAN, is proposed for converting SAR images into multispectral images. In this process, to tackle the issues of noise and image generation quality, a TV-BM3D module is introduced into the generator model. Through TV regularization, block-matching, and 3D filtering, these two modules can preserve the edges and reduce the speckle noise in SAR images. In addition, spectral attention is added to improve the spectral features of the generated MS images. Furthermore, we construct a very high-resolution SAR-to-MS image dataset, S2MS-HR, with a spatial resolution of 0.3 m, which is currently the most comprehensive dataset available for high-resolution SAR-to-MS image interpretation. Finally, a series of experiments are conducted on the relevant dataset. Both quantitative and qualitative evaluations demonstrate that our method outperforms several state-of-the-art models in translation performance. The solution effectively facilitates high-quality transitions of SAR images across different types. Full article

(This article belongs to the Special Issue High Earth Orbit Spaceborne SAR Systems, Technologies, and Applications)

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