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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.

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To meet the radar data requirements of target detection technology research and address the lack of publicly available sea-detecting radar data, a data-sharing program for sea-detecting radar is proposed herein. The aim of the proposed data-sharing program is to conduct sea detection experiments using an X-band solidstate phase-coherent radar and other multi-type radars to obtain the target and sea clutter data under different sea conditions, resolutions, and grazing angles. Moreover, the marine meteorological and hydrological data, target position, and track data are simultaneously obtained using the proposed data-sharing program to help achieve the standardized management of radar-measured data. The proposed data-sharing program aims to promote the open sharing of data sets, serve as the basis for research on sea clutter characteristics, and facilitate the research on sea clutter suppression and target detection technology. To meet the radar data requirements of target detection technology research and address the lack of publicly available sea-detecting radar data, a data-sharing program for sea-detecting radar is proposed herein. The aim of the proposed data-sharing program is to conduct sea detection experiments using an X-band solidstate phase-coherent radar and other multi-type radars to obtain the target and sea clutter data under different sea conditions, resolutions, and grazing angles. Moreover, the marine meteorological and hydrological data, target position, and track data are simultaneously obtained using the proposed data-sharing program to help achieve the standardized management of radar-measured data. The proposed data-sharing program aims to promote the open sharing of data sets, serve as the basis for research on sea clutter characteristics, and facilitate the research on sea clutter suppression and target detection technology.
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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.
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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.
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Electromagnetic waves are transmitted by radars and reflected by different objects, and radar signal processing is highly significant as its analyses can lead to the acquisition of important information such as the situation and radial movement speed. Moreover, deep learning has gained much attention in several fields, and it can be utilized to implement radar signal processing. Compared with the traditional methods, deep learning can realize automatic feature extraction and yield highly accurate results; hence, in this paper, the application of deep learning algorithm in radar signal processing is studied. In addition, the study directions in radar signal processing are summarized into overfitting and interpretation. Thus, these two issues are being considered. Electromagnetic waves are transmitted by radars and reflected by different objects, and radar signal processing is highly significant as its analyses can lead to the acquisition of important information such as the situation and radial movement speed. Moreover, deep learning has gained much attention in several fields, and it can be utilized to implement radar signal processing. Compared with the traditional methods, deep learning can realize automatic feature extraction and yield highly accurate results; hence, in this paper, the application of deep learning algorithm in radar signal processing is studied. In addition, the study directions in radar signal processing are summarized into overfitting and interpretation. Thus, these two issues are being considered.
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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.
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In this paper, the definition and the key features of Software Radar, which is a new concept, are proposed and discussed. We consider the development of modern radar system technology to be divided into three stages: Digital Radar, Software radar and Intelligent Radar, and the second stage is just commencing now. A Software Radar system should be a combination of various modern digital modular components conformed to certain software and hardware standards. Moreover, a software radar system with an open system architecture supporting to decouple application software and low level hardware would be easy to adopt user requirements-oriented developing methodology instead of traditional specific function-oriented developing methodology. Compared with traditional Digital Radar, Software Radar system can be easily reconfigured and scaled up or down to adapt to the changes of requirements and technologies. A demonstration Software Radar signal processing system, RadarLab 2.0, which has been developed by Tsinghua University, is introduced in this paper and the suggestions for the future development of Software Radar in China are also given in the conclusion. In this paper, the definition and the key features of Software Radar, which is a new concept, are proposed and discussed. We consider the development of modern radar system technology to be divided into three stages: Digital Radar, Software radar and Intelligent Radar, and the second stage is just commencing now. A Software Radar system should be a combination of various modern digital modular components conformed to certain software and hardware standards. Moreover, a software radar system with an open system architecture supporting to decouple application software and low level hardware would be easy to adopt user requirements-oriented developing methodology instead of traditional specific function-oriented developing methodology. Compared with traditional Digital Radar, Software Radar system can be easily reconfigured and scaled up or down to adapt to the changes of requirements and technologies. A demonstration Software Radar signal processing system, RadarLab 2.0, which has been developed by Tsinghua University, is introduced in this paper and the suggestions for the future development of Software Radar in China are also given in the conclusion.
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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.
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Cross-eye jamming is an effective angular deception jamming technique used for countering monopulse radars. With the need of countermeasure against active radar seekers, the research on cross-eye jamming becomes a hot research topic in electronic war. This study overviews the cross-eye jamming with regard to jamming theories, equipment, application problems, and current research trends to offer comprehensive knowledge and future research ideas. Cross-eye jamming is an effective angular deception jamming technique used for countering monopulse radars. With the need of countermeasure against active radar seekers, the research on cross-eye jamming becomes a hot research topic in electronic war. This study overviews the cross-eye jamming with regard to jamming theories, equipment, application problems, and current research trends to offer comprehensive knowledge and future research ideas.
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Microwave photonic integrated chip technology is an important supporting technology of microwave photonic radar. It can not only realize the multifunction of devices, reduce the volume of microwave photonic radar, but also greatly improve the stability and reliability. This paper introduces the photonic integrated chip technologies based on the commonly used InP, Si, LiNbO3 and their heterogeneous integrations and the optoelectronic integration chip technologies for microwave photonics. Finally, the future development trends is discussed. Microwave photonic integrated chip technology is an important supporting technology of microwave photonic radar. It can not only realize the multifunction of devices, reduce the volume of microwave photonic radar, but also greatly improve the stability and reliability. This paper introduces the photonic integrated chip technologies based on the commonly used InP, Si, LiNbO3 and their heterogeneous integrations and the optoelectronic integration chip technologies for microwave photonics. Finally, the future development trends is discussed.
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Synthetic Aperture Radar (SAR) technology has undergone two-dimensional, two-and-a-half-dimensional, and three-dimensional SAR. It has also developed to multidimensional SAR and has made great technical achievements. After a brief summary of the development of SAR and its imaging technology, this study proposes the concept of holographic SAR and gives a clear definition of the concept for the first time. Furthermore, it points out the difference and connection between this holographic SAR definition and existing concepts, such as holographic radar, circular tomographic SAR, and multidimensional SAR. On this basis, the imaging system and signal model of holographic SAR are established under the framework of the existing multidimensional SAR, and preliminary imaging ideas are proposed. Thus, a preliminary theoretical and technical framework for the development of holographic SAR technology is provided. Synthetic Aperture Radar (SAR) technology has undergone two-dimensional, two-and-a-half-dimensional, and three-dimensional SAR. It has also developed to multidimensional SAR and has made great technical achievements. After a brief summary of the development of SAR and its imaging technology, this study proposes the concept of holographic SAR and gives a clear definition of the concept for the first time. Furthermore, it points out the difference and connection between this holographic SAR definition and existing concepts, such as holographic radar, circular tomographic SAR, and multidimensional SAR. On this basis, the imaging system and signal model of holographic SAR are established under the framework of the existing multidimensional SAR, and preliminary imaging ideas are proposed. Thus, a preliminary theoretical and technical framework for the development of holographic SAR technology is provided.
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The classical Track Segment Association (TSA) algorithm suffers from low accuracy and is impractical to use in concentrated targets, branching, and cross-tracking environment. Thus, a new statistical binary track segment association algorithm is proposed. The new algorithm is more appropriate as it increases the sample size for the 2 distribution threshold detection. Simulation results show that in air cross tracking and for ballistic targets, the global correct association rate and the average correct association rate of the proposed algorithm are remarkably improved, which proves the good performance of the proposed algorithm. The classical Track Segment Association (TSA) algorithm suffers from low accuracy and is impractical to use in concentrated targets, branching, and cross-tracking environment. Thus, a new statistical binary track segment association algorithm is proposed. The new algorithm is more appropriate as it increases the sample size for the 2 distribution threshold detection. Simulation results show that in air cross tracking and for ballistic targets, the global correct association rate and the average correct association rate of the proposed algorithm are remarkably improved, which proves the good performance of the proposed algorithm.
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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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Flying birds and Unmanned Aerial Vehicles (UAVs) are typical “low, slow, and small” targets with low observability. The need for effective monitoring and identification of these two targets has become urgent and must be solved to ensure the safety of air routes and urban areas. There are many types of flying birds and UAVs that are characterized by low flying heights, strong maneuverability, small radar cross-sectional areas, and complicated detection environments, which are posing great challenges in target detection worldwide. “Visible (high detection ability) and clear-cut (high recognition probability)” methods and technologies must be developed that can finely describe and recognize UAVs, flying birds, and “low-slow-small” targets. This paper reviews the recent progress in research on detection and recognition technologies for rotor UAVs and flying birds in complex scenes and discusses effective detection and recognition methods for the detection of birds and drones, including echo modeling and recognition of fretting characteristics, the enhancement and extraction of maneuvering features in ubiquitous observation mode, distributed multi-view features fusion, differences in motion trajectories, and intelligent classification via deep learning. Lastly, the problems of existing research approaches are summarized, and we consider the future development prospects of target detection and recognition technologies for flying birds and UAVs in complex scenarios. Flying birds and Unmanned Aerial Vehicles (UAVs) are typical “low, slow, and small” targets with low observability. The need for effective monitoring and identification of these two targets has become urgent and must be solved to ensure the safety of air routes and urban areas. There are many types of flying birds and UAVs that are characterized by low flying heights, strong maneuverability, small radar cross-sectional areas, and complicated detection environments, which are posing great challenges in target detection worldwide. “Visible (high detection ability) and clear-cut (high recognition probability)” methods and technologies must be developed that can finely describe and recognize UAVs, flying birds, and “low-slow-small” targets. This paper reviews the recent progress in research on detection and recognition technologies for rotor UAVs and flying birds in complex scenes and discusses effective detection and recognition methods for the detection of birds and drones, including echo modeling and recognition of fretting characteristics, the enhancement and extraction of maneuvering features in ubiquitous observation mode, distributed multi-view features fusion, differences in motion trajectories, and intelligent classification via deep learning. Lastly, the problems of existing research approaches are summarized, and we consider the future development prospects of target detection and recognition technologies for flying birds and UAVs in complex scenarios.
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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.

16

Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) is one of the most powerful Earth observation techniques, especially useful for measuring highly detailed ground deformation over large ground areas. Much research has been carried out to apply MT-InSAR to monitor ground and infrastructure deformation in urban areas related to land reclamation, underground construction and groundwater extraction. This paper reviews the progress in the research and identifies challenges in applying the technology, including the inconsistency in coherent point identification when different approaches are used, the reliability issue in parameter estimation, difficulty in accurate geolocation of measured points, the one-dimensional line-of-sight nature of InSAR measurements, the inability of making complete measurements over an area due to geometric distortions, especially the shadowing effects, the challenges in processing large SAR datasets, the decrease of the number of coherent points with the increase of the length of SAR time series, and the difficulty in quality control of MT-InSAR results.

Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) is one of the most powerful Earth observation techniques, especially useful for measuring highly detailed ground deformation over large ground areas. Much research has been carried out to apply MT-InSAR to monitor ground and infrastructure deformation in urban areas related to land reclamation, underground construction and groundwater extraction. This paper reviews the progress in the research and identifies challenges in applying the technology, including the inconsistency in coherent point identification when different approaches are used, the reliability issue in parameter estimation, difficulty in accurate geolocation of measured points, the one-dimensional line-of-sight nature of InSAR measurements, the inability of making complete measurements over an area due to geometric distortions, especially the shadowing effects, the challenges in processing large SAR datasets, the decrease of the number of coherent points with the increase of the length of SAR time series, and the difficulty in quality control of MT-InSAR results.

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As an important tool for acquiring remote sensing information, Synthetic Aperture Radar (SAR) has various modes, including high-resolution wide-swath, multi-angle information acquisition, high temporal observation, and three-dimensional topographic mapping. For any spaceborne SAR system, obtaining high-quality images is a prerequisite for improving the performance of SAR applications. In this paper, we analyze the factors affecting spaceborne SAR imaging and image quality with respect to orbit, platform, payload, and signal processing. We describe high-precision data acquisition techniques, including amplitude-phase compensation, the dynamic adjustment of the central electronic equipment, and antenna pattern estimation. We then present imaging compensation methods based on the improved motion model and tropospheric delay correction, which can achieve resolutions better than 0.3 m. Lastly, we summarize and compare SAR image processing techniques such as speckle noise suppression, azimuth ambiguity suppression, and sidelobe suppression, whereby the equivalent number of looks can be increased to more than 25 and the azimuth ambiguity and sidelobes can both be suppressed by 20 dB. As an important tool for acquiring remote sensing information, Synthetic Aperture Radar (SAR) has various modes, including high-resolution wide-swath, multi-angle information acquisition, high temporal observation, and three-dimensional topographic mapping. For any spaceborne SAR system, obtaining high-quality images is a prerequisite for improving the performance of SAR applications. In this paper, we analyze the factors affecting spaceborne SAR imaging and image quality with respect to orbit, platform, payload, and signal processing. We describe high-precision data acquisition techniques, including amplitude-phase compensation, the dynamic adjustment of the central electronic equipment, and antenna pattern estimation. We then present imaging compensation methods based on the improved motion model and tropospheric delay correction, which can achieve resolutions better than 0.3 m. Lastly, we summarize and compare SAR image processing techniques such as speckle noise suppression, azimuth ambiguity suppression, and sidelobe suppression, whereby the equivalent number of looks can be increased to more than 25 and the azimuth ambiguity and sidelobes can both be suppressed by 20 dB.
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Array signal processing is an essential tool in broad radar applications. The coprime array has recently been proposed to overcome the bottleneck caused by the Nyquist spatial sampling rate. The coprime array, whose sparse structure and undersampling feature drastically decrease necessary computational and hardware cost, provides a theoretical foundation and technical basis for the increasing demands of its practical applications. Considering its superior performance in degrees-of-freedom, spatial resolution, and computational complexity, research on coprime array signal processing has attracted much attention. This paper reviews recent research progress on coprime array signal processing, which has focused on both the Direction-of-Arrival (DOA) estimation and adaptive beamforming. From the perspective of coprime array DOA estimation, this paper summarizes two typical approaches, namely the coprime subarray decomposition-based approach and the virtual array signal processing-based approach. Moreover, recent work on low-complexity and super-resolution DOA estimation via compressive sensing and gridless techniques is also introduced. From the perspective of coprime array adaptive beamforming, the differences and relationships between DOA estimation and beamforming in the framework of coprime array signal processing are discussed, and an efficient, robust, and adaptive beamformer design tailored for the coprime array is introduced. Advantages and the future directions of coprime array signal processing are discussed, along with the theoretical basis and a technical reference for practical radar applications. Array signal processing is an essential tool in broad radar applications. The coprime array has recently been proposed to overcome the bottleneck caused by the Nyquist spatial sampling rate. The coprime array, whose sparse structure and undersampling feature drastically decrease necessary computational and hardware cost, provides a theoretical foundation and technical basis for the increasing demands of its practical applications. Considering its superior performance in degrees-of-freedom, spatial resolution, and computational complexity, research on coprime array signal processing has attracted much attention. This paper reviews recent research progress on coprime array signal processing, which has focused on both the Direction-of-Arrival (DOA) estimation and adaptive beamforming. From the perspective of coprime array DOA estimation, this paper summarizes two typical approaches, namely the coprime subarray decomposition-based approach and the virtual array signal processing-based approach. Moreover, recent work on low-complexity and super-resolution DOA estimation via compressive sensing and gridless techniques is also introduced. From the perspective of coprime array adaptive beamforming, the differences and relationships between DOA estimation and beamforming in the framework of coprime array signal processing are discussed, and an efficient, robust, and adaptive beamformer design tailored for the coprime array is introduced. Advantages and the future directions of coprime array signal processing are discussed, along with the theoretical basis and a technical reference for practical radar applications.
19
The need of extra wireless spectrum is on the rise, given the rapid development of global wireless communication industry. To this end, Radar and Communication Spectrum Sharing (RCSS) has gained considerable attentions recently from both industry and academia. In particular, RCSS aims not only at enabling the spectral cohabitation of radar and communication systems, but also at designing a novel joint system that is capable of both functionalities. In this paper, a systematic overview of RCSS by focusing on the two main research directions are provided, i.e., Radar-Communication Coexistence (RCC) and Dual-Functional Radar-Communication (DFRC). We commence by discussing the coexistence examples of radar and communication at various frequency bands, and then elaborate on the practical application scenarios of the DFRC techniques. As a further step, the state-of-the-art approaches of both RCC and DFRC are reviewed. Finally we conclude the paper by identifying a number of open problems in the research area of RCSS. The need of extra wireless spectrum is on the rise, given the rapid development of global wireless communication industry. To this end, Radar and Communication Spectrum Sharing (RCSS) has gained considerable attentions recently from both industry and academia. In particular, RCSS aims not only at enabling the spectral cohabitation of radar and communication systems, but also at designing a novel joint system that is capable of both functionalities. In this paper, a systematic overview of RCSS by focusing on the two main research directions are provided, i.e., Radar-Communication Coexistence (RCC) and Dual-Functional Radar-Communication (DFRC). We commence by discussing the coexistence examples of radar and communication at various frequency bands, and then elaborate on the practical application scenarios of the DFRC techniques. As a further step, the state-of-the-art approaches of both RCC and DFRC are reviewed. Finally we conclude the paper by identifying a number of open problems in the research area of RCSS.
20
There is an urgent need for radar-measured data to tackle key technologies of radar maritime target detection. The ‘‘Sea-detecting X-band Radar and Data Acquisition Program’’, proposed in 2019, aims to obtain data through radar experiments and share them publicly. In 2020, the program continued to advance and conducted several experiments in three aspects, namely, Radar Cross-Section (RCS) calibration of radar targets, detection of sea clutter and target under different sea conditions, as well as detection and tracking of maneuvering targets in sea. The measurement data of the stainless steel sphere calibrator at different distances in radar slow-scanning mode, sea clutter in radar staring mode in different directions, sea target in radar staring mode, and marine engine speedboat in radar scanning mode are obtained. In addition, wind and wave data, data from the Automatic Identification System (AIS) of targets, visible/infrared data, and other associated sensor data are synchronously obtained. There is an urgent need for radar-measured data to tackle key technologies of radar maritime target detection. The ‘‘Sea-detecting X-band Radar and Data Acquisition Program’’, proposed in 2019, aims to obtain data through radar experiments and share them publicly. In 2020, the program continued to advance and conducted several experiments in three aspects, namely, Radar Cross-Section (RCS) calibration of radar targets, detection of sea clutter and target under different sea conditions, as well as detection and tracking of maneuvering targets in sea. The measurement data of the stainless steel sphere calibrator at different distances in radar slow-scanning mode, sea clutter in radar staring mode in different directions, sea target in radar staring mode, and marine engine speedboat in radar scanning mode are obtained. In addition, wind and wave data, data from the Automatic Identification System (AIS) of targets, visible/infrared data, and other associated sensor data are synchronously obtained.
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