Most Viewed Abstracts

1
Knowledge of target polarization characteristics is valuable for radar target detection, classification, and identification.We conducted experimental research on an Unmanned Aerial Vehicle (UAV) with complex materials and structures to determine the differences in polarimetric scattering between the UAV and its perfect electric conductor model.To illustrate the coherence of the entire UAV and its components using polarimetric scattering, we measured and analyzed each part.The results reveal that the airframe and aerofoils directly influence the depolarization, and that the polarimetric scattering characteristics of the airframe represent the primary source for the whole UAV. Knowledge of target polarization characteristics is valuable for radar target detection, classification, and identification.We conducted experimental research on an Unmanned Aerial Vehicle (UAV) with complex materials and structures to determine the differences in polarimetric scattering between the UAV and its perfect electric conductor model.To illustrate the coherence of the entire UAV and its components using polarimetric scattering, we measured and analyzed each part.The results reveal that the airframe and aerofoils directly influence the depolarization, and that the polarimetric scattering characteristics of the airframe represent the primary source for the whole UAV.
2
Spaceborne SAR, which is a kind of initiatively microwave imaging sensor, plays an important role in gathering information with its capability of all-day and all-weather imaging, and has become an indispensable sensor for observing the earth. With the development of SAR techniques, Spaceborne SAR has been provided with the ability of High-Resolution Wide-Swath, miniaturization with low cost, bistatic and multi-mode imaging, and Ground Moving Target Indicating (GMTI), so more accurate information about the culture could be obtained with lower cost. In the meantime, more technique problems with muliti-mode, new work system and complex environment are arising and needed to be solved. The main work of this paper is discussing the current situation and the future development of Spaceborne SAR. Spaceborne SAR, which is a kind of initiatively microwave imaging sensor, plays an important role in gathering information with its capability of all-day and all-weather imaging, and has become an indispensable sensor for observing the earth. With the development of SAR techniques, Spaceborne SAR has been provided with the ability of High-Resolution Wide-Swath, miniaturization with low cost, bistatic and multi-mode imaging, and Ground Moving Target Indicating (GMTI), so more accurate information about the culture could be obtained with lower cost. In the meantime, more technique problems with muliti-mode, new work system and complex environment are arising and needed to be solved. The main work of this paper is discussing the current situation and the future development of Spaceborne SAR.
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Over the recent years, deep-learning technology has been widely used. However, in research based on Synthetic Aperture Radar (SAR) ship target detection, it is difficult to support the training of a deep-learning network model because of the difficulty in data acquisition and the small scale of the samples. This paper provides a SAR ship detection dataset with a high resolution and large-scale images. This dataset comprises 31 images from Gaofen-3 satellite SAR images, including harbors, islands, reefs, and the sea surface in different conditions. The backgrounds include various scenarios such as the near shore and open sea. We conducted experiments using both traditional detection algorithms and deep-learning algorithms and observed the densely connected end-to-end neural network to achieve the highest average precision of 88.1%. Based on the experiments and performance analysis, corresponding benchmarks are provided as a basis for further research on SAR ship detection using this dataset.

Over the recent years, deep-learning technology has been widely used. However, in research based on Synthetic Aperture Radar (SAR) ship target detection, it is difficult to support the training of a deep-learning network model because of the difficulty in data acquisition and the small scale of the samples. This paper provides a SAR ship detection dataset with a high resolution and large-scale images. This dataset comprises 31 images from Gaofen-3 satellite SAR images, including harbors, islands, reefs, and the sea surface in different conditions. The backgrounds include various scenarios such as the near shore and open sea. We conducted experiments using both traditional detection algorithms and deep-learning algorithms and observed the densely connected end-to-end neural network to achieve the highest average precision of 88.1%. Based on the experiments and performance analysis, corresponding benchmarks are provided as a basis for further research on SAR ship detection using this dataset.

4
Spaceborne Synthetic Aperture Radar (SAR), which can be mounted on space vehicles to collect information of the entire planet with all-day and all-weather imaging capacity, has been an indispensable device for earth observation. Currently, the technology of our spaceborne SAR has achieved a considerable technological improvement, including the resolution change from meter to submeter, the imaging mode from stripmap to azimuth beam steering like the sliding spotlight, the practical application of the multichannel approach and the conversion of single polarization into full polarization. With the development of SAR techniques, forthcoming SAR will make breakthroughs in SAR architectures, concepts, technologies and modes, for example, high-resolution wide-swath imaging, multistatic SAR, payload miniaturization and intelligence. All of these will extend the observation dimensions and obtain multidimensional data. This study focuses on the forthcoming development of spaceborne SAR. Spaceborne Synthetic Aperture Radar (SAR), which can be mounted on space vehicles to collect information of the entire planet with all-day and all-weather imaging capacity, has been an indispensable device for earth observation. Currently, the technology of our spaceborne SAR has achieved a considerable technological improvement, including the resolution change from meter to submeter, the imaging mode from stripmap to azimuth beam steering like the sliding spotlight, the practical application of the multichannel approach and the conversion of single polarization into full polarization. With the development of SAR techniques, forthcoming SAR will make breakthroughs in SAR architectures, concepts, technologies and modes, for example, high-resolution wide-swath imaging, multistatic SAR, payload miniaturization and intelligence. All of these will extend the observation dimensions and obtain multidimensional data. This study focuses on the forthcoming development of spaceborne SAR.
5
Video Synthetic Aperture Radar (SAR) provides dynamic information about an observation scene in a video to the human eye, which can be very useful for the real-time detection of the ground maneuvering targets. The focusing of video SAR data is demanding because of its high data rate. In this study, we discuss suitable focusing algorithms and presents the obtained simulation results. Further, the shadow formation mechanism is analyzed with respect to target detection. Finally, the machine learning algorithm used for detecting the shadows of the moving targets is compared with the classical image processing methods that use real datasets. Video Synthetic Aperture Radar (SAR) provides dynamic information about an observation scene in a video to the human eye, which can be very useful for the real-time detection of the ground maneuvering targets. The focusing of video SAR data is demanding because of its high data rate. In this study, we discuss suitable focusing algorithms and presents the obtained simulation results. Further, the shadow formation mechanism is analyzed with respect to target detection. Finally, the machine learning algorithm used for detecting the shadows of the moving targets is compared with the classical image processing methods that use real datasets.
6
Specific emitter identification is a technique of extracting the radio frequency fingerprints of the received electromagnetic signal only using external feature measurements to determine the specific emitter that transmits the signal. In recent years, the related theories and practical applications of specific emitter identification have been continuously improved, and research on radio frequency fingerprinting feature extraction methods has made great progress. Based on the domestic and foreign academic achievements, this paper systematically reviews the status quo of the fingerprint feature extraction method of specific emitter identification. In addition, a new feature classification framework is proposed based on the inherent logic of fingerprint feature extraction. The classification framework combines the description characteristics of different radio frequency fingerprinting features and the correlation between them. It divides the existing radio frequency features into two main categories: direct measurement features and dimensionality reduction transform features, which have three levels. Finally, this paper analyzes and explores several potential research directions of fingerprint feature extraction, aiming to benefit the research and application of specific radiation source identification. Specific emitter identification is a technique of extracting the radio frequency fingerprints of the received electromagnetic signal only using external feature measurements to determine the specific emitter that transmits the signal. In recent years, the related theories and practical applications of specific emitter identification have been continuously improved, and research on radio frequency fingerprinting feature extraction methods has made great progress. Based on the domestic and foreign academic achievements, this paper systematically reviews the status quo of the fingerprint feature extraction method of specific emitter identification. In addition, a new feature classification framework is proposed based on the inherent logic of fingerprint feature extraction. The classification framework combines the description characteristics of different radio frequency fingerprinting features and the correlation between them. It divides the existing radio frequency features into two main categories: direct measurement features and dimensionality reduction transform features, which have three levels. Finally, this paper analyzes and explores several potential research directions of fingerprint feature extraction, aiming to benefit the research and application of specific radiation source identification.
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Synthetic Aperture Radar three-Dimensional (SAR 3D) imaging technology can eliminate severe overlap in 2D images, and improve target recognition and 3D modeling capabilities, which have become an important trend in SAR development. After decades of development of SAR 3D imaging technology, many types of 3D imaging methods have been proposed. In this study, the history of SAR 3D imaging technology is systematically reviewed and the characteristics of existing SAR 3D imaging technology are analyzed. Given that the 3D information contained in SAR echo and images is not fully used by existing techniques, a new concept of SAR microwave vision 3D imaging has been proposed for the first time. This new concept is integrated with microwave scattering mechanism and image visual semantics to realize three-dimensional reconstruction, which form the theory and method of SAR microwave vision 3D imaging and can achieve high-efficiency and low-cost SAR 3D imaging. This study also analyzes the concept, goal and key scientific problems of SAR microwave vision 3D imaging and provides a preliminary solution, which will contribute in several ways to our understanding of SAR 3D imaging and provide the basis for further research.

Synthetic Aperture Radar three-Dimensional (SAR 3D) imaging technology can eliminate severe overlap in 2D images, and improve target recognition and 3D modeling capabilities, which have become an important trend in SAR development. After decades of development of SAR 3D imaging technology, many types of 3D imaging methods have been proposed. In this study, the history of SAR 3D imaging technology is systematically reviewed and the characteristics of existing SAR 3D imaging technology are analyzed. Given that the 3D information contained in SAR echo and images is not fully used by existing techniques, a new concept of SAR microwave vision 3D imaging has been proposed for the first time. This new concept is integrated with microwave scattering mechanism and image visual semantics to realize three-dimensional reconstruction, which form the theory and method of SAR microwave vision 3D imaging and can achieve high-efficiency and low-cost SAR 3D imaging. This study also analyzes the concept, goal and key scientific problems of SAR microwave vision 3D imaging and provides a preliminary solution, which will contribute in several ways to our understanding of SAR 3D imaging and provide the basis for further research.

8
The technique of radar feature extraction, imaging, and recognition of target with micro-motions has become one of the most potential research directions in the field of radar target accurate recognition. In this paper, the concept of micro-motion is first introduced briefly. Subsequently, the achievements of echo modeling, feature extraction, imaging, and identification of micro-motion targets are summarized. Several typical frontier applications are then introduced. Finally, the future development trends of the research are discussed. The technique of radar feature extraction, imaging, and recognition of target with micro-motions has become one of the most potential research directions in the field of radar target accurate recognition. In this paper, the concept of micro-motion is first introduced briefly. Subsequently, the achievements of echo modeling, feature extraction, imaging, and identification of micro-motion targets are summarized. Several typical frontier applications are then introduced. Finally, the future development trends of the research are discussed.
9
For the fast detection of ships in large-scale remote sensing images, a cascade convolutional neural network is proposed, which is a cascade combination of two Fully Convolutional Neural networks (FCNs), the target FCN for Prescreening (P-FCN), and the target FCN for Detection (D-FCN). The P-FCN is a lightweight image classification network that is responsible for the rapid pre-screening of possible ship areas in large-scale images. The region proposals generated by the P-FCN have less redundancy, which can reduce the computational burden of the D-FCN. The D-FCN is an improved U-Net that can accurately detect arbitrary-oriented ships by adding target masks and ship orientation estimation layers to the traditional U-Net structure for multitask learning. In our experiment, TerraSAR-X remote sensing images and the optical remote sensing images obtained from the 91 satellite map software and the DOTA dataset were used to test the network. The results show that the detection accuracy of our method was 0.928 and 0.926 for synthetic aperture radar images and optical images, respectively, which were close to the performance of the traditional sliding window method. However, the running time of the proposed method was only about 1/3 of that of the sliding window method. Therefore, the cascade convolutional neural network can significantly improve the target detection efficiency while maintaining the detection accuracy and can realize the rapid detection of ship targets in large-scale remote sensing images. For the fast detection of ships in large-scale remote sensing images, a cascade convolutional neural network is proposed, which is a cascade combination of two Fully Convolutional Neural networks (FCNs), the target FCN for Prescreening (P-FCN), and the target FCN for Detection (D-FCN). The P-FCN is a lightweight image classification network that is responsible for the rapid pre-screening of possible ship areas in large-scale images. The region proposals generated by the P-FCN have less redundancy, which can reduce the computational burden of the D-FCN. The D-FCN is an improved U-Net that can accurately detect arbitrary-oriented ships by adding target masks and ship orientation estimation layers to the traditional U-Net structure for multitask learning. In our experiment, TerraSAR-X remote sensing images and the optical remote sensing images obtained from the 91 satellite map software and the DOTA dataset were used to test the network. The results show that the detection accuracy of our method was 0.928 and 0.926 for synthetic aperture radar images and optical images, respectively, which were close to the performance of the traditional sliding window method. However, the running time of the proposed method was only about 1/3 of that of the sliding window method. Therefore, the cascade convolutional neural network can significantly improve the target detection efficiency while maintaining the detection accuracy and can realize the rapid detection of ship targets in large-scale remote sensing images.
10
Starting from the detection principle and characteristics of passive radar, this paper describes the development of passive radar based on the low frequency band (HF/VHF/UHF) digital broadcasting and TV signal. Based on the radio coverage ratio and technical features of digital broadcasting and TV signals, the research status in abroad, especially in Europe, is introduced at first, on experimental systems, technical parameters, and comparative experiments. Then the latest development of passive radars, in different frequency bands in China, both theory and experimental study are presented. Followed is the commentary on the key techniques and problems of Digital Broadcasting-based Passive Radar (DBPR), including the waveforms properties and its modification, reference signal extraction, multipath clutter rejection, target detection, tracking, and fusion as well as real-time signal processing. Finally, the prospects of development and application of this kind of passive radar are discussed. Starting from the detection principle and characteristics of passive radar, this paper describes the development of passive radar based on the low frequency band (HF/VHF/UHF) digital broadcasting and TV signal. Based on the radio coverage ratio and technical features of digital broadcasting and TV signals, the research status in abroad, especially in Europe, is introduced at first, on experimental systems, technical parameters, and comparative experiments. Then the latest development of passive radars, in different frequency bands in China, both theory and experimental study are presented. Followed is the commentary on the key techniques and problems of Digital Broadcasting-based Passive Radar (DBPR), including the waveforms properties and its modification, reference signal extraction, multipath clutter rejection, target detection, tracking, and fusion as well as real-time signal processing. Finally, the prospects of development and application of this kind of passive radar are discussed.
11
Terahertz radar has unique advantages, including large bandwidth, high resolution, Doppler sensitivity, and anti-interference; it is a significant development in the field of target detection. Herein, the history of electronic and optical terahertz radar systems is introduced, and the current situation and latest progress pertaining to these systems are reviewed. The target characteristics of terahertz radar are summarized based on its mechanism, calculation, and measurement. Moreover, the current research status of terahertz SAR, ISAR, array, and aperture encoding imaging are discussed, and the applications of terahertz radar, such as early warning detection and security anti-terrorism systems, are briefly introduced. Finally, the development direction of terahertz radar technology is forecast. Terahertz radar has unique advantages, including large bandwidth, high resolution, Doppler sensitivity, and anti-interference; it is a significant development in the field of target detection. Herein, the history of electronic and optical terahertz radar systems is introduced, and the current situation and latest progress pertaining to these systems are reviewed. The target characteristics of terahertz radar are summarized based on its mechanism, calculation, and measurement. Moreover, the current research status of terahertz SAR, ISAR, array, and aperture encoding imaging are discussed, and the applications of terahertz radar, such as early warning detection and security anti-terrorism systems, are briefly introduced. Finally, the development direction of terahertz radar technology is forecast.
12

Circular Synthetic Aperture Radar (CSAR) is a novel imaging mode, which has the advantages of all-directional observation, high spatial resolution, and three-dimensional imaging. With the development of airborne CSAR imaging techniques, it has become one of the effective methods for key point area observation. This paper introduces works on airborne CSAR imaging techniques performed by our research team in recent years, including airborne CSAR imaging mode, spatial resolution evaluation, two-dimensional CSAR imaging, three-dimensional target image reconstruction based on a single CSAR, and three-dimensional holographic SAR imaging. In this paper, experimental results based on raw data acquired using airborne CSAR systems with P and X bands are presented. The obtained research results prove the effectivity and practicability of the airborne CSAR imaging mode. The content of this paper is based on a keynote speech presented by the author at the Fifth Young Scientists Forum of Journal of Radars on August 15, 2019.

Circular Synthetic Aperture Radar (CSAR) is a novel imaging mode, which has the advantages of all-directional observation, high spatial resolution, and three-dimensional imaging. With the development of airborne CSAR imaging techniques, it has become one of the effective methods for key point area observation. This paper introduces works on airborne CSAR imaging techniques performed by our research team in recent years, including airborne CSAR imaging mode, spatial resolution evaluation, two-dimensional CSAR imaging, three-dimensional target image reconstruction based on a single CSAR, and three-dimensional holographic SAR imaging. In this paper, experimental results based on raw data acquired using airborne CSAR systems with P and X bands are presented. The obtained research results prove the effectivity and practicability of the airborne CSAR imaging mode. The content of this paper is based on a keynote speech presented by the author at the Fifth Young Scientists Forum of Journal of Radars on August 15, 2019.

13

Deep learning such as deep neural networks has revolutionized the computer vision area. Deep learning-based algorithms have surpassed conventional algorithms in terms of performance by a significant margin. This paper reviews our works in the application of deep convolutional neural networks to target recognition and terrain classification using the SAR image. A convolutional neural network is employed to automatically extract a hierarchic feature representation from the data, based on which the target recognition and terrain classification can be conducted. Experimental results on the MSTAR benchmark dataset reveal that deep convolutional network could achieve a state-of-the-art classification accuracy of 99% for the 10-class task. For a polarimetric SAR image classification, we propose complex-valued convolutional neural networks for complex SAR images. This algorithm achieved a state-of-the-art accuracy of 95% for the 15-class task on the Flevoland benchmark dataset.

Deep learning such as deep neural networks has revolutionized the computer vision area. Deep learning-based algorithms have surpassed conventional algorithms in terms of performance by a significant margin. This paper reviews our works in the application of deep convolutional neural networks to target recognition and terrain classification using the SAR image. A convolutional neural network is employed to automatically extract a hierarchic feature representation from the data, based on which the target recognition and terrain classification can be conducted. Experimental results on the MSTAR benchmark dataset reveal that deep convolutional network could achieve a state-of-the-art classification accuracy of 99% for the 10-class task. For a polarimetric SAR image classification, we propose complex-valued convolutional neural networks for complex SAR images. This algorithm achieved a state-of-the-art accuracy of 95% for the 15-class task on the Flevoland benchmark dataset.

14
Multi-aspect SAR is a new SAR mode that has two advantages, i.e., long-term observations and a large synthetic-aperture azimuth angle. Previous studies have reported that these unique advantages enable even single-channel systems to have a relatively strong capability for detecting moving targets, i.e., multi-aspect SAR expands and improves the moving-target-related capabilities of the earlier SAR satellite system without increasing its complexity. As such, multi-aspect SAR-GMTI has become a trending topic for research. After reviewing the recent progress and research basis of multi-aspect SAR-GMTI, in this paper, we present our research on the Gaofen-3 SAR, which includes: moving-target detection methods that use the staring spotlight mode, dual-channels GMTI mode, and the dual-channel spotlight GMTI mode. With the results obtained by this research, we hope to establish a basis for the engineering implementation of current and future spaceborne single-channel SAR-GMTI modes and the design of a future spaceborne multi-aspect SAR mode capable of retrieving time-series and dynamic scene information. Multi-aspect SAR is a new SAR mode that has two advantages, i.e., long-term observations and a large synthetic-aperture azimuth angle. Previous studies have reported that these unique advantages enable even single-channel systems to have a relatively strong capability for detecting moving targets, i.e., multi-aspect SAR expands and improves the moving-target-related capabilities of the earlier SAR satellite system without increasing its complexity. As such, multi-aspect SAR-GMTI has become a trending topic for research. After reviewing the recent progress and research basis of multi-aspect SAR-GMTI, in this paper, we present our research on the Gaofen-3 SAR, which includes: moving-target detection methods that use the staring spotlight mode, dual-channels GMTI mode, and the dual-channel spotlight GMTI mode. With the results obtained by this research, we hope to establish a basis for the engineering implementation of current and future spaceborne single-channel SAR-GMTI modes and the design of a future spaceborne multi-aspect SAR mode capable of retrieving time-series and dynamic scene information.
15
The antenna pattern uncertainty is the main error of SAR system. The technique for inflight antenna pattern measurement of spaceborne SAR is one of the most important technique of SAR calibration. This paper discusses the development courses of the inflight antenna pattern measurement of spaceborne SAR, analyses its development trend and compares the main inflight antenna pattern measurement techniques. This paper will be an important reference for designing a project of inflight antenna pattern measurement of spaceborne SAR. The antenna pattern uncertainty is the main error of SAR system. The technique for inflight antenna pattern measurement of spaceborne SAR is one of the most important technique of SAR calibration. This paper discusses the development courses of the inflight antenna pattern measurement of spaceborne SAR, analyses its development trend and compares the main inflight antenna pattern measurement techniques. This paper will be an important reference for designing a project of inflight antenna pattern measurement of spaceborne SAR.
16
Viewing from the interaction between external and internal causes on the time scale of history, present and future, this paper analyzes and demonstrates the developing motivation and stage characteristics of radar technology. The external causes are interpreted as target, environment and mission, and the internal causes as information acquisition pattern, realization ability and resource utilization. The fundamental law of radar development is revealed as evolving stepwise from lower into higher dimension of detection through the aromorphosis of channel configuration, viewing angle and signal dimensionality, while the main innovation strategies of radar technology are summarized as modifying information acquisition pattern, enhancing realization ability and increasing utilized resources. Furthermore, the developing trends and main characteristics of future radar technology are deduced, and proposals for promoting future innovation and development are also presented. Viewing from the interaction between external and internal causes on the time scale of history, present and future, this paper analyzes and demonstrates the developing motivation and stage characteristics of radar technology. The external causes are interpreted as target, environment and mission, and the internal causes as information acquisition pattern, realization ability and resource utilization. The fundamental law of radar development is revealed as evolving stepwise from lower into higher dimension of detection through the aromorphosis of channel configuration, viewing angle and signal dimensionality, while the main innovation strategies of radar technology are summarized as modifying information acquisition pattern, enhancing realization ability and increasing utilized resources. Furthermore, the developing trends and main characteristics of future radar technology are deduced, and proposals for promoting future innovation and development are also presented.
17
In this paper, the development requirements and challenges of phased array radar design are discussed. A new architecture of phased array radar based on microwave photonic technology is proposed, and its technical advantages are explained. Aiming for applications in engineering practice, the main scientific problems and major technical challenges currently faced are concisely presented from the aspects of their core components, basic transmission links, various processing units, and overall systems. The road map of follow-up research work is given and the future development in this field is finally prospected. In this paper, the development requirements and challenges of phased array radar design are discussed. A new architecture of phased array radar based on microwave photonic technology is proposed, and its technical advantages are explained. Aiming for applications in engineering practice, the main scientific problems and major technical challenges currently faced are concisely presented from the aspects of their core components, basic transmission links, various processing units, and overall systems. The road map of follow-up research work is given and the future development in this field is finally prospected.
18
The vortex electromagnetic wave, which carries the Orbital Angular Momentum (OAM), reflects a new degree of freedom in addition to the traditional degrees of freedom such as intensity, phase, frequency, and polarization. Theoretically, vortex electromagnetic wave, at any frequency, has an infinite number of orthogonal modes that do not interfere with each other, and in recent years, they have shown important potential applications in the fields of radar imaging, wireless communication and so on. Therefore, they have attracted considerable attention from scholars worldwide owing to their high research value and application prospects. Here, this paper mainly introduces the recent research advances on the antenna technology of vortex electromagnetic wave, including single microstrip patch antenna, array antenna, traveling wave antenna, and metasurface antenna structure. The single microstrip patch antenna is widely used owing to its simple structure and low manufacturing cost. The traveling wave antenna can generate multi-OAM mode vortex electromagnetic waves in a wide-frequency range. The array antenna is easy to design and controllably generate high-gain OAM electromagnetic waves with different modes. The metasurface antennas do not require complex feeding networks, which has the advantage of a lower profile of the antenna. Finally, we summarize these four common vortex antennas and further look forward to their future developments. The vortex electromagnetic wave, which carries the Orbital Angular Momentum (OAM), reflects a new degree of freedom in addition to the traditional degrees of freedom such as intensity, phase, frequency, and polarization. Theoretically, vortex electromagnetic wave, at any frequency, has an infinite number of orthogonal modes that do not interfere with each other, and in recent years, they have shown important potential applications in the fields of radar imaging, wireless communication and so on. Therefore, they have attracted considerable attention from scholars worldwide owing to their high research value and application prospects. Here, this paper mainly introduces the recent research advances on the antenna technology of vortex electromagnetic wave, including single microstrip patch antenna, array antenna, traveling wave antenna, and metasurface antenna structure. The single microstrip patch antenna is widely used owing to its simple structure and low manufacturing cost. The traveling wave antenna can generate multi-OAM mode vortex electromagnetic waves in a wide-frequency range. The array antenna is easy to design and controllably generate high-gain OAM electromagnetic waves with different modes. The metasurface antennas do not require complex feeding networks, which has the advantage of a lower profile of the antenna. Finally, we summarize these four common vortex antennas and further look forward to their future developments.
19
As a new radar technology, the distributed aperture coherent radar is expected to be the next generation radar, which is easier to transport and less expensive than the traditional large aperture radar. However, the time synchronization and phase synchronization are key issues to be addressed for the distributed aperture coherent radar. In this paper, the error sources of time synchronization and phase synchronization are analyzed, and the corresponding mathematical models are first derived. Then, the impact of synchronization errors on the coherent performance is simulated, and the accuracy of time and phase synchronization is presented based on the simulation results. Finally, the noncorrelation transmission scheme and the calibration scheme based on the wired transmission are proposed to realize the time and phase synchronization, respectively. Research of the synchronization problem could be very helpful to realize the new radar technology of distributed aperture coherent radar. As a new radar technology, the distributed aperture coherent radar is expected to be the next generation radar, which is easier to transport and less expensive than the traditional large aperture radar. However, the time synchronization and phase synchronization are key issues to be addressed for the distributed aperture coherent radar. In this paper, the error sources of time synchronization and phase synchronization are analyzed, and the corresponding mathematical models are first derived. Then, the impact of synchronization errors on the coherent performance is simulated, and the accuracy of time and phase synchronization is presented based on the simulation results. Finally, the noncorrelation transmission scheme and the calibration scheme based on the wired transmission are proposed to realize the time and phase synchronization, respectively. Research of the synchronization problem could be very helpful to realize the new radar technology of distributed aperture coherent radar.
20
In recent years, Orthogonal Frequency Division Multiplexing (OFDM) signal has been widely used in Synthetic Aperture Radar (SAR) imaging research due to its orthogonality and large bandwidth. Compared with the traditional SAR, OFDM SAR has certain advantages in imaging applications because of its unique signal characteristics. Nevertheless, OFDM SAR faces many challenges. In this paper, on the basis of different antenna configurations, the problems and studies of single-antenna OFDM SAR imaging and multi-antenna MIMO OFDM SAR imaging are reviewed. The imaging methods of SAR/MIMO SAR based on OFDM and cyclic prefix OFDM signals are discussed, and some possible future research directions of OFDM SAR are presented. In recent years, Orthogonal Frequency Division Multiplexing (OFDM) signal has been widely used in Synthetic Aperture Radar (SAR) imaging research due to its orthogonality and large bandwidth. Compared with the traditional SAR, OFDM SAR has certain advantages in imaging applications because of its unique signal characteristics. Nevertheless, OFDM SAR faces many challenges. In this paper, on the basis of different antenna configurations, the problems and studies of single-antenna OFDM SAR imaging and multi-antenna MIMO OFDM SAR imaging are reviewed. The imaging methods of SAR/MIMO SAR based on OFDM and cyclic prefix OFDM signals are discussed, and some possible future research directions of OFDM SAR are presented.
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