Most Cited

(The cited data comes from the whole network and is updated monthly.)
1
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.
2
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.
3
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.
4

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.

5
Circular SAR (CSAR) is a newly developed all-directional high resolution 3D imaging mode in recent years, to satisfy the demand of finer observation. The National Key Laboratory of Science and Technology on Microwave Imaging, Institute of Electronics, Chinese Academy of Sciences (MITL, IECAS), had the first test flight experiment in Aug. 2011 with a P-band full polarization SAR system, and successfully obtained the all-directional high resolution circular SAR image. The initial results show that CSAR technique has the encouraging potential capability in the fields of high precision mapping, disaster evaluation, resource management and the other related applications. This paper firstly makes a detailed discussion on the progress of circular SAR imaging technique, which emphases on the several airborne experiments performed these years to show CSARs attractive features, then studies and illustrates the key techniques, and finally discusses the development trends. Circular SAR (CSAR) is a newly developed all-directional high resolution 3D imaging mode in recent years, to satisfy the demand of finer observation. The National Key Laboratory of Science and Technology on Microwave Imaging, Institute of Electronics, Chinese Academy of Sciences (MITL, IECAS), had the first test flight experiment in Aug. 2011 with a P-band full polarization SAR system, and successfully obtained the all-directional high resolution circular SAR image. The initial results show that CSAR technique has the encouraging potential capability in the fields of high precision mapping, disaster evaluation, resource management and the other related applications. This paper firstly makes a detailed discussion on the progress of circular SAR imaging technique, which emphases on the several airborne experiments performed these years to show CSARs attractive features, then studies and illustrates the key techniques, and finally discusses the development trends.
6
This study presents a new method of Synthetic Aperture Radar (SAR) image target recognition based on a convolutional neural network. First, we introduce a class separability measure into the cost function to improve this network's ability to distinguish between categories. Then, we extract SAR image features using the improved convolutional neural network and classify these features using a support vector machine. Experimental results using moving and stationary target acquisition and recognition SAR datasets prove the validity of this method. This study presents a new method of Synthetic Aperture Radar (SAR) image target recognition based on a convolutional neural network. First, we introduce a class separability measure into the cost function to improve this network's ability to distinguish between categories. Then, we extract SAR image features using the improved convolutional neural network and classify these features using a support vector machine. Experimental results using moving and stationary target acquisition and recognition SAR datasets prove the validity of this method.
7
This paper first reviews the history and trends in the development of spaceborne Synthetic Aperture Radar (SAR) satellite technology in the USA and Europe. The basic information regarding launched satellites and future satellite plans are introduced. Then, this paper summarizes and categorizes the imaging algorithms of spaceborn SAR satellites, and analyzes the advantages and disadvantages of each algorithm. Next, the scope and the application status of each algorithm are presented. Then, the paper presents details of trends related to the SAR imaging algorithm, which mainly introduces the algorithms based on compressive sensing theory and new image modes. The simulation results are also presented. Finally, we summarize the development direction of the spaceborne SAR imaging algorithm. This paper first reviews the history and trends in the development of spaceborne Synthetic Aperture Radar (SAR) satellite technology in the USA and Europe. The basic information regarding launched satellites and future satellite plans are introduced. Then, this paper summarizes and categorizes the imaging algorithms of spaceborn SAR satellites, and analyzes the advantages and disadvantages of each algorithm. Next, the scope and the application status of each algorithm are presented. Then, the paper presents details of trends related to the SAR imaging algorithm, which mainly introduces the algorithms based on compressive sensing theory and new image modes. The simulation results are also presented. Finally, we summarize the development direction of the spaceborne SAR imaging algorithm.
8
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.
9
Automatic Target Recognition (ATR) is one of the most difficult problems in Synthetic Aperture Radar (SAR) data interpretation. In recent years, the model-based SAR target recognition method has attracted much attention because of its good performance in the extended operation condition. Based on the research of a few domestic research institutes, this paper briefly introduces the preliminary research results and gives some thoughts about SAR ATR problem. First of all, the development of parametric scattering model are discussed from three aspects. Next, two ways to model the parametric electromagnetic scattering for complex target are put forward. Finally, we propose a new framework for a Three-Dimensional (3D) parametric scattering model based SAR ATR. In the end, the future research direction of model-based SAR target recognition is prospected. Automatic Target Recognition (ATR) is one of the most difficult problems in Synthetic Aperture Radar (SAR) data interpretation. In recent years, the model-based SAR target recognition method has attracted much attention because of its good performance in the extended operation condition. Based on the research of a few domestic research institutes, this paper briefly introduces the preliminary research results and gives some thoughts about SAR ATR problem. First of all, the development of parametric scattering model are discussed from three aspects. Next, two ways to model the parametric electromagnetic scattering for complex target are put forward. Finally, we propose a new framework for a Three-Dimensional (3D) parametric scattering model based SAR ATR. In the end, the future research direction of model-based SAR target recognition is prospected.
10
In the field of image processing using Synthetic Aperture Radar (SAR), aircraft detection is a challenging task. Conventional approaches always extract targets from the background of an image using image segmentation methods. Nevertheless, these methods mainly focus on pixel contrast and neglect the integrity of the target, which leads to locating the object inaccurately. In this study, we build a novel SAR aircraft detection framework. Compared to traditional methods, an improved saliency-based method is proposed to locate candidates coarsely and quickly in large scenes. This proposed method is verified to be more efficient compared with the sliding window method. Next, we design a convolutional neural network fitting in SAR images to accurately identify the candidates and obtain the final detection result. Moreover, to overcome the problem of limited available SAR data, we propose four data augmentation methods comprising translation, speckle noising, contrast enhancement, and small-angle rotation. Experimental results show that our framework achieves excellent performance on the high-resolution TerraSAR-X dataset. In the field of image processing using Synthetic Aperture Radar (SAR), aircraft detection is a challenging task. Conventional approaches always extract targets from the background of an image using image segmentation methods. Nevertheless, these methods mainly focus on pixel contrast and neglect the integrity of the target, which leads to locating the object inaccurately. In this study, we build a novel SAR aircraft detection framework. Compared to traditional methods, an improved saliency-based method is proposed to locate candidates coarsely and quickly in large scenes. This proposed method is verified to be more efficient compared with the sliding window method. Next, we design a convolutional neural network fitting in SAR images to accurately identify the candidates and obtain the final detection result. Moreover, to overcome the problem of limited available SAR data, we propose four data augmentation methods comprising translation, speckle noising, contrast enhancement, and small-angle rotation. Experimental results show that our framework achieves excellent performance on the high-resolution TerraSAR-X dataset.
11
Sea clutter is one of the main limiting factors influencing the target detection performance of nautical radars. The physical mechanism of sea clutter is complex with an abundance of influencing factors, and the non-Gaussian as well as non-stationarity behavior is significant. Thus, research into sea clutter property cognition is complicated and has to be systematic. Based on research that concentrates on experimental data, this paper reviews and summarizes the research developments in sea clutter property cognition. It concentrates on the properties that are of most interest for target detection algorithms:amplitude distribution, spectra, correlation, and non-stationarity and nonlinearity. The main research results are also concluded. Based on this, four aspects of problems that need further exploration are highlighted and include the following:further analysis of sea clutter influencing factors; the game problem between sea clutter precision modeling and the requirements of detection algorithms; and the property cognition between radar target and sea clutter. Sea clutter is one of the main limiting factors influencing the target detection performance of nautical radars. The physical mechanism of sea clutter is complex with an abundance of influencing factors, and the non-Gaussian as well as non-stationarity behavior is significant. Thus, research into sea clutter property cognition is complicated and has to be systematic. Based on research that concentrates on experimental data, this paper reviews and summarizes the research developments in sea clutter property cognition. It concentrates on the properties that are of most interest for target detection algorithms:amplitude distribution, spectra, correlation, and non-stationarity and nonlinearity. The main research results are also concluded. Based on this, four aspects of problems that need further exploration are highlighted and include the following:further analysis of sea clutter influencing factors; the game problem between sea clutter precision modeling and the requirements of detection algorithms; and the property cognition between radar target and sea clutter.
12
This paper gives the experimental research of HF Passive Bistatic Radar (HFPBR) based on Digital Radio Mondiale (DRM) digital AM broadcasting that have been first carried out in China, using the newly-developed all-digital active/passive integrated HF surface wave radar system. The principle, key techniques, experimental equipment, and preliminary results are introduced about this new radar system. Based on analysis of the measurement data, experimental results under different scenarios including surface-wave, sky-wave, and hybrid sky-surface propagation modes are presented, which have proved, for the first time worldwide, the technical feasibility of using DRM broadcasting signal for over-the-horizon detection by field experiment and formed the theoretical and experimental basis for the further development of HFPBR. This paper gives the experimental research of HF Passive Bistatic Radar (HFPBR) based on Digital Radio Mondiale (DRM) digital AM broadcasting that have been first carried out in China, using the newly-developed all-digital active/passive integrated HF surface wave radar system. The principle, key techniques, experimental equipment, and preliminary results are introduced about this new radar system. Based on analysis of the measurement data, experimental results under different scenarios including surface-wave, sky-wave, and hybrid sky-surface propagation modes are presented, which have proved, for the first time worldwide, the technical feasibility of using DRM broadcasting signal for over-the-horizon detection by field experiment and formed the theoretical and experimental basis for the further development of HFPBR.
13
Radar polarimetry is an applied fundamental science field that is focused on understanding interaction processes between radar waves and targets and disclosing their mechanisms. Radar polarimetry has significant application prospects in the fields of microwave remote sensing, earth observation, meteorological measurement, battlefield reconnaissance, anti-interference, target recognition, and so on. This study briefly reviews the development history of radar polarization theory and technology. Next, the state of the art of several key technologies within radar polarimetry, including the precise acquisition of radar polarization information, polarization-sensitive array signal processing, target polarization characteristics, polarization antiinterference, and target polarization classification and recognition, is summarized. Finally, the future developments of radar polarization technology are considered. Radar polarimetry is an applied fundamental science field that is focused on understanding interaction processes between radar waves and targets and disclosing their mechanisms. Radar polarimetry has significant application prospects in the fields of microwave remote sensing, earth observation, meteorological measurement, battlefield reconnaissance, anti-interference, target recognition, and so on. This study briefly reviews the development history of radar polarization theory and technology. Next, the state of the art of several key technologies within radar polarimetry, including the precise acquisition of radar polarization information, polarization-sensitive array signal processing, target polarization characteristics, polarization antiinterference, and target polarization classification and recognition, is summarized. Finally, the future developments of radar polarization technology are considered.
14
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.
15
GF-3, the first full-polarimetric Synthetic Aperture Radar (SAR) satellite of China with a resolution up to 1 m, was successfully launched in August 2016 and, after 5 months of in-orbit calibration, it was officially delivered to the users in January 2017. In this paper, the geometric positioning error sources of the entire system are analyzed based on the real data acquisition, including atmospheric transmission, image processing, and geometric positioning. The positioning precision of the SAR system is validated by corner reflectors. The results show that the satellite positioning accuracy improved by 3 m. GF-3, the first full-polarimetric Synthetic Aperture Radar (SAR) satellite of China with a resolution up to 1 m, was successfully launched in August 2016 and, after 5 months of in-orbit calibration, it was officially delivered to the users in January 2017. In this paper, the geometric positioning error sources of the entire system are analyzed based on the real data acquisition, including atmospheric transmission, image processing, and geometric positioning. The positioning precision of the SAR system is validated by corner reflectors. The results show that the satellite positioning accuracy improved by 3 m.
16
Synthetic Aperture Radar (SAR) image processing requires huge computation amount. Traditionally, this task runs on the workstation or server based on Central Processing Unit (CPU) and is rather time-consuming, hence real-time processing of SAR data is impossible. Based on Compute Unified Device Architecture (CUDA) technology, a new plan of SAR imaging algorithm operated on NVIDIA Graphic Processing Unit (GPU) is proposed. The new proposal makes it possible that the data processing procedure and CPU/GPU data exchanging execute concurrently, especially when SAR data size exceeds total GPU global memory size. Multi-GPU is suitably supported by the new proposal and all of computational resources are fully exploited. It is shown by experiment on NVIDIA K20C and INTEL E5645 that the proposed solution accelerates SAR data processing by tens of times. Consequently, the GPU based SAR processing system with the proposed solution embedded is much more power saving and portable, which makes it qualified to be a real-time SAR data processing system. Experiment shows that SAR data of 36 Mega points can be processed in real-time per second by K20C with the new solution equipped. Synthetic Aperture Radar (SAR) image processing requires huge computation amount. Traditionally, this task runs on the workstation or server based on Central Processing Unit (CPU) and is rather time-consuming, hence real-time processing of SAR data is impossible. Based on Compute Unified Device Architecture (CUDA) technology, a new plan of SAR imaging algorithm operated on NVIDIA Graphic Processing Unit (GPU) is proposed. The new proposal makes it possible that the data processing procedure and CPU/GPU data exchanging execute concurrently, especially when SAR data size exceeds total GPU global memory size. Multi-GPU is suitably supported by the new proposal and all of computational resources are fully exploited. It is shown by experiment on NVIDIA K20C and INTEL E5645 that the proposed solution accelerates SAR data processing by tens of times. Consequently, the GPU based SAR processing system with the proposed solution embedded is much more power saving and portable, which makes it qualified to be a real-time SAR data processing system. Experiment shows that SAR data of 36 Mega points can be processed in real-time per second by K20C with the new solution equipped.
17
Attributed scattering center is one of important features of Synthetic Aperture Radar (SAR) image. In this paper, a method for the matching of attributed scattering centers and its application to SAR target recognition is proposed. First, the attributed scattering centers of the test SAR image and template SAR images are extracted on the basis of the attributed scattering model. Second, the Hungarian algorithm is employed to match the two scattering center sets. Based on the one to one correspondence, we design a new similarity measure to evaluate the similarity between the two scattering center sets that will decide the target type of the test image. The similarity measure considers the effects of each individual scattering center, single matching pair, and missing alarms and false alarms; thus, it is more comprehensive. The experiment based on moving and stationary target acquisition and recognition database demonstrates the validity of the proposed method. Attributed scattering center is one of important features of Synthetic Aperture Radar (SAR) image. In this paper, a method for the matching of attributed scattering centers and its application to SAR target recognition is proposed. First, the attributed scattering centers of the test SAR image and template SAR images are extracted on the basis of the attributed scattering model. Second, the Hungarian algorithm is employed to match the two scattering center sets. Based on the one to one correspondence, we design a new similarity measure to evaluate the similarity between the two scattering center sets that will decide the target type of the test image. The similarity measure considers the effects of each individual scattering center, single matching pair, and missing alarms and false alarms; thus, it is more comprehensive. The experiment based on moving and stationary target acquisition and recognition database demonstrates the validity of the proposed method.
18
For the high-speed, high-maneuverability and stealthy target detection via modern radar in complicated electromagnetic environment, a novel radar signal processing approach called Space-Time-Frequency Focus-Before-Detection (STF-FBD) via multi-dimensional coherent integration is proposed. Based on space-timefrequency signal modeling for modern radar systems, the proposed method can effectively suppress the strong interference, such as clutter and active jamming, and overcome the problems of scaled effect of high-speed targets, aperture fill time, sparse frequency sub-band synthesis, across range units, across Doppler units and across beam units. The proposed methods improves radar signal processing performance on the steps like energy integration, target detection, parameter estimation, maneuver tracking, feature extraction and target recognition. It also outperforms the existing Track-Before-Detection (TBD) methods and establish a unified STF-FBD and STF-FBD-TBD radar signal processing frame work. The proposed method is suitable for high-speed, high-maneuverability and stealthy target, as well as for conventional targets. It is applicable for new-generation modern radar, as well as for conventional radars, and may find application to different field. For the high-speed, high-maneuverability and stealthy target detection via modern radar in complicated electromagnetic environment, a novel radar signal processing approach called Space-Time-Frequency Focus-Before-Detection (STF-FBD) via multi-dimensional coherent integration is proposed. Based on space-timefrequency signal modeling for modern radar systems, the proposed method can effectively suppress the strong interference, such as clutter and active jamming, and overcome the problems of scaled effect of high-speed targets, aperture fill time, sparse frequency sub-band synthesis, across range units, across Doppler units and across beam units. The proposed methods improves radar signal processing performance on the steps like energy integration, target detection, parameter estimation, maneuver tracking, feature extraction and target recognition. It also outperforms the existing Track-Before-Detection (TBD) methods and establish a unified STF-FBD and STF-FBD-TBD radar signal processing frame work. The proposed method is suitable for high-speed, high-maneuverability and stealthy target, as well as for conventional targets. It is applicable for new-generation modern radar, as well as for conventional radars, and may find application to different field.
19
Micro-Doppler signature is one of the physical characteristics of the target. The radar signature of a target with micro-motion can make fine characterizations of the shape, structure, and moving state of target, which reflects the nonstationary property of a radar signal. Hence, it has great superiority in the analysis of sea clutter and target detection in the case of high sea states based on the micro-Doppler theory. In this paper, to show the need for micro-Doppler, the modeling of scattering clutter from time-varying sea surface and analysis methods of sea clutter Doppler are first reviewed based on the principles and characteristics of micro-Doppler. Then, applications and technological approaches of micro-Doppler in sea surface target detection are introduced from the perspective of micro-motion target modeling and detection methods of micro-motion signatures. Finally, future research interests are highlighted based on problems experienced in present studies. Micro-Doppler signature is one of the physical characteristics of the target. The radar signature of a target with micro-motion can make fine characterizations of the shape, structure, and moving state of target, which reflects the nonstationary property of a radar signal. Hence, it has great superiority in the analysis of sea clutter and target detection in the case of high sea states based on the micro-Doppler theory. In this paper, to show the need for micro-Doppler, the modeling of scattering clutter from time-varying sea surface and analysis methods of sea clutter Doppler are first reviewed based on the principles and characteristics of micro-Doppler. Then, applications and technological approaches of micro-Doppler in sea surface target detection are introduced from the perspective of micro-motion target modeling and detection methods of micro-motion signatures. Finally, future research interests are highlighted based on problems experienced in present studies.
20
Global Navigation Satellite System (GNSS), has a significant impact on all areas of human activity, not only can provide users with shared global navigation, position and timing information, but also can provide a L-band microwave signal source of long term stability and high temporal-spatial resolution. In recent years, development of the navigation satellite remote sensing applications using GNSS as a external illuminator, it has been forming a new Global Navigation Satellite System METeorology (GNSS/MET), of which Global Navigation Satellite System-Reflection (GNSS-R) signals remote sensing technology is rising. It could be considered as a non-cooperative artificial illuminator, bistatic (multi-static) radar system, and has the advantages of both passive and active remote sensing. Then it gets more and more peoples attention and favor, and broadening into Atmosphere -ocean and land surface remote sensing fields. However, the address of this technology is very messy at home and abroad, and not able to accurately express its special meaning. This article attempts to give a new term: Exogenous-Aided Remote Sensing (EARS) for discussion. Global Navigation Satellite System (GNSS), has a significant impact on all areas of human activity, not only can provide users with shared global navigation, position and timing information, but also can provide a L-band microwave signal source of long term stability and high temporal-spatial resolution. In recent years, development of the navigation satellite remote sensing applications using GNSS as a external illuminator, it has been forming a new Global Navigation Satellite System METeorology (GNSS/MET), of which Global Navigation Satellite System-Reflection (GNSS-R) signals remote sensing technology is rising. It could be considered as a non-cooperative artificial illuminator, bistatic (multi-static) radar system, and has the advantages of both passive and active remote sensing. Then it gets more and more peoples attention and favor, and broadening into Atmosphere -ocean and land surface remote sensing fields. However, the address of this technology is very messy at home and abroad, and not able to accurately express its special meaning. This article attempts to give a new term: Exogenous-Aided Remote Sensing (EARS) for discussion.
  • First
  • Prev
  • 1
  • 2
  • 3
  • 4
  • 5
  • Last
  • Total:27
  • To
  • Go