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1
2018, 7(5): 531-547.
Abstract
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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.
2
2018, 7(5): 565-574.
In this paper, Convolutional Neural Networks (CNN) are used to detect and classify micro-Doppler effects of maritime targets by using generalized learning ability for high-dimensional features. Based on the micro-motion model of maritime targets, two-dimensional time-frequency maps of four types of micro-motion signals are constructed in the measured sea clutter background. These maps were used as training and test datasets. Furthermore, three types of CNN models, i.e., LeNet, AlexNet, and GoogleNet, are used in binary detection and multiple micro-motion classifications. The effects of signal-to-noise ratio on detection and classification performance are also studied. Compared with the traditional support vector machine method, the proposed method can learn the micro-motion features intelligently, and has performed better in detection and classification. Thus, this study can provide a new technical approach for radar target detection and recognition under a cluttered background.
In this paper, Convolutional Neural Networks (CNN) are used to detect and classify micro-Doppler effects of maritime targets by using generalized learning ability for high-dimensional features. Based on the micro-motion model of maritime targets, two-dimensional time-frequency maps of four types of micro-motion signals are constructed in the measured sea clutter background. These maps were used as training and test datasets. Furthermore, three types of CNN models, i.e., LeNet, AlexNet, and GoogleNet, are used in binary detection and multiple micro-motion classifications. The effects of signal-to-noise ratio on detection and classification performance are also studied. Compared with the traditional support vector machine method, the proposed method can learn the micro-motion features intelligently, and has performed better in detection and classification. Thus, this study can provide a new technical approach for radar target detection and recognition under a cluttered background.
3
2018, 7(2): 153-166.
Unlike the conventional phased array that provides only angle-dependent transmit beampattern, Frequency Diverse Array (FDA) employs a small frequency increment across its array elements to produce automatic beam scanning without requiring phase shifters or mechanical steering. FDA can produce both range-dependent and time-variant transmit beampatterns, which overcomes the disadvantages of conventional phased arrays that produce only angle-dependent beampattern. Thus, FDA has many promising applications. Based on a previous study conducted by the author, " Frequency Diverse Array Radar: Concept, Principle and Application” (Journal of Electronics & Information Technology, 2016, 38(4): 1000–1011), the current study introduces basic FDA radar concepts, principles, and application characteristics and reviews recent advances on FDA radar and its applications. In addition, several new promising applications of FDA technology are discussed, such as radar electronic warfare and radar-communications, as well as open technical challenges such as beampattern variance, effective receiver design, adaptive signal detection and estimation, and the implementation of practical FDA radar demos.
Unlike the conventional phased array that provides only angle-dependent transmit beampattern, Frequency Diverse Array (FDA) employs a small frequency increment across its array elements to produce automatic beam scanning without requiring phase shifters or mechanical steering. FDA can produce both range-dependent and time-variant transmit beampatterns, which overcomes the disadvantages of conventional phased arrays that produce only angle-dependent beampattern. Thus, FDA has many promising applications. Based on a previous study conducted by the author, " Frequency Diverse Array Radar: Concept, Principle and Application” (Journal of Electronics & Information Technology, 2016, 38(4): 1000–1011), the current study introduces basic FDA radar concepts, principles, and application characteristics and reviews recent advances on FDA radar and its applications. In addition, several new promising applications of FDA technology are discussed, such as radar electronic warfare and radar-communications, as well as open technical challenges such as beampattern variance, effective receiver design, adaptive signal detection and estimation, and the implementation of practical FDA radar demos.
4
2018, 7(4): 395-411.
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.
5
2018, 7(2): 167-182.
The carrier frequencies of array elements in a Frequency Diverse Array (FDA) radar are slightly distinguished, leading to a range-angle-time-dependent transmit beampattern. Thus, an FDA radar carries additional information in a certain range and provides more flexibility in signal processing and new technical issues. FDA is covered by scope of the general waveform diversity concept. This paper overviews the state-of-the-art FDA technology and its radar applications. From the viewpoint of the general radar system theory, we mainly introduce the coherent FDA and orthogonal FDA frameworks. The orthogonal FDA is also referred to as Multiple-Input Multiple-Output (MIMO) radar using FDA or FDA-MIMO radar. Key applications in anti-jamming and issues related with range ambiguity are addressed. We also outline the challenges in FDA radar applications and several interesting research topics.
The carrier frequencies of array elements in a Frequency Diverse Array (FDA) radar are slightly distinguished, leading to a range-angle-time-dependent transmit beampattern. Thus, an FDA radar carries additional information in a certain range and provides more flexibility in signal processing and new technical issues. FDA is covered by scope of the general waveform diversity concept. This paper overviews the state-of-the-art FDA technology and its radar applications. From the viewpoint of the general radar system theory, we mainly introduce the coherent FDA and orthogonal FDA frameworks. The orthogonal FDA is also referred to as Multiple-Input Multiple-Output (MIMO) radar using FDA or FDA-MIMO radar. Key applications in anti-jamming and issues related with range ambiguity are addressed. We also outline the challenges in FDA radar applications and several interesting research topics.
6
2018, 7(1): 1-21.
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.
7
2018, 7(6): 633-654.
Conventional Synthetic Aperture Radar (SAR) moves along a straight line and forms a linear synthetic apertures. It can only obtain the two-dimensional (2-D) image of illuminated scene that is the projection of the three-dimensional (3-D) real scene onto a slant plane. The slant plane 2-D SAR image, however, suffers from layover and foreshortening effects. 3-D SAR imaging enables 3-D resolving capability by extending the acquisition of frequency information from 2-D to 3-D. It can obtain the 3-D distribution of scattering centers; therefore, it solves the geometric deformation problems of layover and foreshortening. 3-D SAR imaging has become a trending topic in research on SAR techniques worldwide. In this paper, we first introduced the concept of 3-D SAR imaging and several typical 3-D SAR imaging modes. Furthermore, it provides a discussion on research progress at home and abroad, particularly focusing on the progress of our research team. Finally, future research prospects are presented.
Conventional Synthetic Aperture Radar (SAR) moves along a straight line and forms a linear synthetic apertures. It can only obtain the two-dimensional (2-D) image of illuminated scene that is the projection of the three-dimensional (3-D) real scene onto a slant plane. The slant plane 2-D SAR image, however, suffers from layover and foreshortening effects. 3-D SAR imaging enables 3-D resolving capability by extending the acquisition of frequency information from 2-D to 3-D. It can obtain the 3-D distribution of scattering centers; therefore, it solves the geometric deformation problems of layover and foreshortening. 3-D SAR imaging has become a trending topic in research on SAR techniques worldwide. In this paper, we first introduced the concept of 3-D SAR imaging and several typical 3-D SAR imaging modes. Furthermore, it provides a discussion on research progress at home and abroad, particularly focusing on the progress of our research team. Finally, future research prospects are presented.
8
2018, 7(5): 557-564.
Classification of drones is important due to their increasing popularity and potential threats. The micro-Doppler signatures that depend on the rotation of rotor blades facilitate the classification of drones. To enhance the robustness of micro-Doppler based classification of drones, dual radar sensing classification scheme is proposed in this paper. First, time-frequency spectrograms are obtained by performing a short-time Fourier transform on the radar data collected by two radar sensors that have similar angular diversity. Then, principal components analysis is utilized to extract the features from the time-frequency spectrograms and the features obtained by the two radar sensors are fused together. Finally, the classification results are obtained by using the support vector machine. The experimental results show that the classification accuracy obtained by the fusion of dual radar sensors is 5% higher than that obtained by only using a single radar sensor.
Classification of drones is important due to their increasing popularity and potential threats. The micro-Doppler signatures that depend on the rotation of rotor blades facilitate the classification of drones. To enhance the robustness of micro-Doppler based classification of drones, dual radar sensing classification scheme is proposed in this paper. First, time-frequency spectrograms are obtained by performing a short-time Fourier transform on the radar data collected by two radar sensors that have similar angular diversity. Then, principal components analysis is utilized to extract the features from the time-frequency spectrograms and the features obtained by the two radar sensors are fused together. Finally, the classification results are obtained by using the support vector machine. The experimental results show that the classification accuracy obtained by the fusion of dual radar sensors is 5% higher than that obtained by only using a single radar sensor.
9
2018, 7(1): 46-55.
In this paper, we review the recent developments on information metamaterials, including digital metamaterials, coding metamaterials, and programmable metamaterials; furthermore, we discuss their applications in the terahertz (THz)-frequency region. In addition their flexibility to manipulate the electromagnetic waves, the physical principle, numerical simulation, fabrication, and application of information metamaterial are discussed in detail. Moreover, we developed and applied a coding metasurface that works in the THz band. Furthermore, the principle of real-time programmable metamaterials and their application in novel imaging systems and radar systems are illustrated. Information metamaterials and metasurfaces can be used for various functional devices such as beam splitting and low radar cross section, which open up a novel route to manipulate THz radiations.
In this paper, we review the recent developments on information metamaterials, including digital metamaterials, coding metamaterials, and programmable metamaterials; furthermore, we discuss their applications in the terahertz (THz)-frequency region. In addition their flexibility to manipulate the electromagnetic waves, the physical principle, numerical simulation, fabrication, and application of information metamaterial are discussed in detail. Moreover, we developed and applied a coding metasurface that works in the THz band. Furthermore, the principle of real-time programmable metamaterials and their application in novel imaging systems and radar systems are illustrated. Information metamaterials and metasurfaces can be used for various functional devices such as beam splitting and low radar cross section, which open up a novel route to manipulate THz radiations.
10
2018, 7(5): 585-592.
In this paper, experimental results of micro-Doppler effect on a multi-rotor drone with digital television based passive radar are discussed. First, the bistatic passive radar micro-motion model of the drone is established. Second, key techniques of micro-motion signal extraction are briefly described. Finally, the experimental process is introduced, including experimental scene configuration and analysis of typical experimental results of micro-Doppler effect. The experimental results agree with the theoretical analysis of the motion parameters of the drone, thereby confirming the technical feasibility of detecting the micro-Doppler effect of the multi-rotor drone using the digital television based passive radar.
In this paper, experimental results of micro-Doppler effect on a multi-rotor drone with digital television based passive radar are discussed. First, the bistatic passive radar micro-motion model of the drone is established. Second, key techniques of micro-motion signal extraction are briefly described. Finally, the experimental process is introduced, including experimental scene configuration and analysis of typical experimental results of micro-Doppler effect. The experimental results agree with the theoretical analysis of the motion parameters of the drone, thereby confirming the technical feasibility of detecting the micro-Doppler effect of the multi-rotor drone using the digital television based passive radar.
11
2018, 7(2): 183-193.
To meet the urgent demand of low-observable moving target detection in complex environments, a novel method of Frequency Diverse Array (FDA) radar signal processing method based on Space-Rang-Doppler Focusing (SRDF) is proposed in this paper. The current development status of the FDA radar, the design of the array structure, beamforming, and joint estimation of distance and angle are systematically reviewed. The extra degrees of freedom provided by FDA radar are fully utilizsed, which include the Degrees Of Freedom (DOFs) of the transmitted waveform, the location of array elements, correlation of beam azimuth and distance, and the long dwell time, which are also the DOFs in joint spatial (angle), distance, and frequency (Doppler) dimensions. Simulation results show that the proposed method has the potential of improving target detection and parameter estimation for weak moving targets in complex environments and has broad application prospects in clutter and interference suppression, moving target refinement, etc..
To meet the urgent demand of low-observable moving target detection in complex environments, a novel method of Frequency Diverse Array (FDA) radar signal processing method based on Space-Rang-Doppler Focusing (SRDF) is proposed in this paper. The current development status of the FDA radar, the design of the array structure, beamforming, and joint estimation of distance and angle are systematically reviewed. The extra degrees of freedom provided by FDA radar are fully utilizsed, which include the Degrees Of Freedom (DOFs) of the transmitted waveform, the location of array elements, correlation of beam azimuth and distance, and the long dwell time, which are also the DOFs in joint spatial (angle), distance, and frequency (Doppler) dimensions. Simulation results show that the proposed method has the potential of improving target detection and parameter estimation for weak moving targets in complex environments and has broad application prospects in clutter and interference suppression, moving target refinement, etc..
12
2018, 7(4): 514-522.
Long Term Evolution (LTE) is a new type of illuminators of opportunity for passive radars, with the advantages of broad bandwidth, high coverage, and strong generality. In this paper, the ambiguity function of Frequency Division Duplexing Long Term Evolution (FDD-LTE) signal is analyzed as an illuminator of opportunity. According to the measured signal, it was found that it is necessary to suppress the inter-frame ambiguity strips in the ambiguity function. Furthermore, themechanism of these inter-frame ambiguity strips was analyzed in detail, which revealed that the LTE signal frame structure is the main factor that causes these inter-frame ambiguity strips and is the major energy source of coherent integration. Thus, a method based on Orthogonal Frequency Division Multiplexing (OFDM) symbol subcarrier coefficient normalization is proposed to suppress these inter-frame ambiguity strips. Simulation and experimental results show that the method can suppress inter-frame ambiguity strips effectively, but does not affect coherent integration, which is the foundation of target detection.
Long Term Evolution (LTE) is a new type of illuminators of opportunity for passive radars, with the advantages of broad bandwidth, high coverage, and strong generality. In this paper, the ambiguity function of Frequency Division Duplexing Long Term Evolution (FDD-LTE) signal is analyzed as an illuminator of opportunity. According to the measured signal, it was found that it is necessary to suppress the inter-frame ambiguity strips in the ambiguity function. Furthermore, themechanism of these inter-frame ambiguity strips was analyzed in detail, which revealed that the LTE signal frame structure is the main factor that causes these inter-frame ambiguity strips and is the major energy source of coherent integration. Thus, a method based on Orthogonal Frequency Division Multiplexing (OFDM) symbol subcarrier coefficient normalization is proposed to suppress these inter-frame ambiguity strips. Simulation and experimental results show that the method can suppress inter-frame ambiguity strips effectively, but does not affect coherent integration, which is the foundation of target detection.
13
2018, 7(2): 194-201.
To accurately identify the range of each target, traditional Multiple-Input Multiple-Output (MIMO) radar techniques not only require designing a shift matrix to describe different range bins but also a large number of snapshots.To alleviate this problem, a multidimensional parameter estimation method based on sparse iteration is proposed for a MIMO radar with Frequency Diverse Array (FDA).The FDA-MIMO radar uses small frequency increments across the array elements, and its transmit steering vector is a function of both range and angle.On the basis of the feature of the FDA-MIMO radar, we consider a weighted lq (0 q 1) minimization problem that is solved using a sparse iterative algorithm.Finally, the target parameters (the amplitude, range, and angle) are obtained using a single snapshot.Moreover, numerical simulations are used to demonstrate the superior performance of the proposed method compared with those of DAS, IAA, and IAA-R.
To accurately identify the range of each target, traditional Multiple-Input Multiple-Output (MIMO) radar techniques not only require designing a shift matrix to describe different range bins but also a large number of snapshots.To alleviate this problem, a multidimensional parameter estimation method based on sparse iteration is proposed for a MIMO radar with Frequency Diverse Array (FDA).The FDA-MIMO radar uses small frequency increments across the array elements, and its transmit steering vector is a function of both range and angle.On the basis of the feature of the FDA-MIMO radar, we consider a weighted lq (0 q 1) minimization problem that is solved using a sparse iterative algorithm.Finally, the target parameters (the amplitude, range, and angle) are obtained using a single snapshot.Moreover, numerical simulations are used to demonstrate the superior performance of the proposed method compared with those of DAS, IAA, and IAA-R.
14
2018, 7(1): 22-45.
With years of development and accumulation, a considerable amount of research has focused on micro-motion, an important auxiliary feature in radar target detection and recognition. With the recent rise of terahertz, micro-motion feature extraction in the terahertz region has increasingly highlighted its advantages. Herein, we systematically surveyed the recent research on terahertz radar micro-motion feature extraction and discussed micro-motion feature analysis, micro-motion feature extraction, and micro-motion target imaging. And then we emphatically introduced the work of our research team, including the theoretical and experimental research on micro-motion feature analysis, micro-motion feature extraction and high-resolution/high-frame micro-motion target imaging. Furthermore, we analyzed the growing trend of micro-motion feature extraction in the terahertz region, and pointed out the new technology directions worth to be studied further and the technical challenges to be solved.
With years of development and accumulation, a considerable amount of research has focused on micro-motion, an important auxiliary feature in radar target detection and recognition. With the recent rise of terahertz, micro-motion feature extraction in the terahertz region has increasingly highlighted its advantages. Herein, we systematically surveyed the recent research on terahertz radar micro-motion feature extraction and discussed micro-motion feature analysis, micro-motion feature extraction, and micro-motion target imaging. And then we emphatically introduced the work of our research team, including the theoretical and experimental research on micro-motion feature analysis, micro-motion feature extraction and high-resolution/high-frame micro-motion target imaging. Furthermore, we analyzed the growing trend of micro-motion feature extraction in the terahertz region, and pointed out the new technology directions worth to be studied further and the technical challenges to be solved.
15
2018, 7(6): 717-729.
In this study, we adopt a criterion of Barker code to generate a high-resolution image from sparse flight samples to establish a three-dimensional (3-D) imaging model of airborne array SAR. Under the condition of motion error, we utilize the Modified Uniformly Redundant Arrays (MURA) modulation and 3-D Back Projection (BP) algorithm to obtain 3-D complex image pairs under each flight. Based on interferometry and Compressed Sensing (CS) in frequency domain, the array deformation error compensation is realized. The phases of 3-D complex image formed by the echo corresponding to negative MURA modulation are referred to perform phase compensation on each single-pass complex image to restore the image phase relation of each flight. Coherent accumulation of each complex image is implemented to realize high-resolution 3-D imaging under sparse flight sampling. Simulation analysis and experimental data verify the feasibility of the proposed method.
In this study, we adopt a criterion of Barker code to generate a high-resolution image from sparse flight samples to establish a three-dimensional (3-D) imaging model of airborne array SAR. Under the condition of motion error, we utilize the Modified Uniformly Redundant Arrays (MURA) modulation and 3-D Back Projection (BP) algorithm to obtain 3-D complex image pairs under each flight. Based on interferometry and Compressed Sensing (CS) in frequency domain, the array deformation error compensation is realized. The phases of 3-D complex image formed by the echo corresponding to negative MURA modulation are referred to perform phase compensation on each single-pass complex image to restore the image phase relation of each flight. Coherent accumulation of each complex image is implemented to realize high-resolution 3-D imaging under sparse flight sampling. Simulation analysis and experimental data verify the feasibility of the proposed method.
16
2018, 7(3): 275-284.
Ultra-WideBand (UWB) radar can reconstruct the layout of a building, providing rich information for detecting and locating humans in buildings. Traditional imaging methods suffer from serious sidelobes and location displacement of behind-the-wall target because of the influence of walls. Sparse recovery is introduced into the field of through-the-wall imaging to improve the imaging quality. However, the reconstruction probability of weak scattering targets is low in traditional methods. In this study, the combination of sparse recovery method and Coherence Factor (CF) weighting is proposed to improve the reconstruction probability of weak scattering targets inside a room. The quasi-establishment of the support set can be improved during sparse imaging by reducing the effect of the sidelobes of strong scattering targets with CF, ultimately enhancing the robustness of the sparse imaging of the building layout. A location correction model for multiple walls after sparse imaging is established, based on which the locating error of walls can be reduced with a low amount of calculation. The results of the measured data reveal that compared with the traditional generalized orthogonal matching pursuit method, the proposed methods can improve the reconstruction probability of weak scattering targets and reduce the locating error of the inner layouts of buildings to less than 10 cm.
Ultra-WideBand (UWB) radar can reconstruct the layout of a building, providing rich information for detecting and locating humans in buildings. Traditional imaging methods suffer from serious sidelobes and location displacement of behind-the-wall target because of the influence of walls. Sparse recovery is introduced into the field of through-the-wall imaging to improve the imaging quality. However, the reconstruction probability of weak scattering targets is low in traditional methods. In this study, the combination of sparse recovery method and Coherence Factor (CF) weighting is proposed to improve the reconstruction probability of weak scattering targets inside a room. The quasi-establishment of the support set can be improved during sparse imaging by reducing the effect of the sidelobes of strong scattering targets with CF, ultimately enhancing the robustness of the sparse imaging of the building layout. A location correction model for multiple walls after sparse imaging is established, based on which the locating error of walls can be reduced with a low amount of calculation. The results of the measured data reveal that compared with the traditional generalized orthogonal matching pursuit method, the proposed methods can improve the reconstruction probability of weak scattering targets and reduce the locating error of the inner layouts of buildings to less than 10 cm.
17
2018, 7(3): 376-386.
This paper examines the processing of millimeter-wave imaging data based on sparse sampling and sparse array design for the rapid imaging of human security data. First, based on the cylindrical scanning imaging model, the Barker code-based randomly sparse sampling method is employed to reduce the scanning time. Then, a three-dimensional imaging algorithm based on interferometry and compressed sensing in the frequency domain is proposed, with sparse representation of the image in the frequency domain after interferometry and Compressed Sensing measurement model, to recover the image frequency spectrum, thereby implementing human security image reconstruction via sparse sampling. Real data processing results indicated that the proposed method could obtain image resolution and performance similar to those of complete samples and that the image correlation coefficients before and after sparse sampling were better than 0.9, with 50% time/data reduction. Furthermore, based on the Barker codes and multistatic work mode, a sparse array architecture for rapid imaging was designed with a sparse rate of 94.6% and the guarantee of imaging quality. The proposed method was found to considerably increase the passage rate and reduce the amount of radiation unit and system complexity, marking its application significance and market prospect in security clearance.
This paper examines the processing of millimeter-wave imaging data based on sparse sampling and sparse array design for the rapid imaging of human security data. First, based on the cylindrical scanning imaging model, the Barker code-based randomly sparse sampling method is employed to reduce the scanning time. Then, a three-dimensional imaging algorithm based on interferometry and compressed sensing in the frequency domain is proposed, with sparse representation of the image in the frequency domain after interferometry and Compressed Sensing measurement model, to recover the image frequency spectrum, thereby implementing human security image reconstruction via sparse sampling. Real data processing results indicated that the proposed method could obtain image resolution and performance similar to those of complete samples and that the image correlation coefficients before and after sparse sampling were better than 0.9, with 50% time/data reduction. Furthermore, based on the Barker codes and multistatic work mode, a sparse array architecture for rapid imaging was designed with a sparse rate of 94.6% and the guarantee of imaging quality. The proposed method was found to considerably increase the passage rate and reduce the amount of radiation unit and system complexity, marking its application significance and market prospect in security clearance.
18
2018, 7(4): 487-497.
A method for fine resolution and high precision Digital Elevation Model (DEM) generation using ascending and descending pass TerraSAR-X/TanDEM-X (TSX/TDX) datasets is proposed in this study. First, the NonLocal Interferometric SAR (NL-InSAR) can effectively generate ascending and descending pass raw DEMs. On this basis, the coherence well recovered by NL-InSAR is used to fusion the raw DEMs to further improve the accuracy and reduce the invalids caused by layover and shadows. This method was used to process the TSX/TDX data obtained in Beijing. The number of invalid points of DEM after fusion decreased significantly. Statistics result shows that it decreased from 4.93% in ascending raw DEM and 4.52% in descending raw DEM to 1.34% in the fusion DEM. At the same time, the accuracy of the fusion DEM increased by 9.6% compared to 6.67 m in the descending raw DEM and 8.7% compared to 6.74 m in the ascending raw DEM, reaching 6.09 m.
A method for fine resolution and high precision Digital Elevation Model (DEM) generation using ascending and descending pass TerraSAR-X/TanDEM-X (TSX/TDX) datasets is proposed in this study. First, the NonLocal Interferometric SAR (NL-InSAR) can effectively generate ascending and descending pass raw DEMs. On this basis, the coherence well recovered by NL-InSAR is used to fusion the raw DEMs to further improve the accuracy and reduce the invalids caused by layover and shadows. This method was used to process the TSX/TDX data obtained in Beijing. The number of invalid points of DEM after fusion decreased significantly. Statistics result shows that it decreased from 4.93% in ascending raw DEM and 4.52% in descending raw DEM to 1.34% in the fusion DEM. At the same time, the accuracy of the fusion DEM increased by 9.6% compared to 6.67 m in the descending raw DEM and 8.7% compared to 6.74 m in the ascending raw DEM, reaching 6.09 m.
19
2018, 7(6): 676-684.
Near-field 3-D imaging based on a scanning array is an important application of Synthetic Aperture Radar (SAR) 3-D imaging technology for civil use. Compared with Single-Input-Single-Output (SISO) arrays, a Multi-Input-Multi-Output (MIMO) scanning system is a special imaging method characterized by high imaging quality, high array efficiency, loose requirements for antenna spacing and low cost. In this paper, two imaging regimes, namely, MIMO-planar scanning and MIMO cylindrical scanning, are described in terms of signal models, imaging algorithms, experimental systems, and imaging results. The results show the great application potential of the imaging technology in various scenarios.
Near-field 3-D imaging based on a scanning array is an important application of Synthetic Aperture Radar (SAR) 3-D imaging technology for civil use. Compared with Single-Input-Single-Output (SISO) arrays, a Multi-Input-Multi-Output (MIMO) scanning system is a special imaging method characterized by high imaging quality, high array efficiency, loose requirements for antenna spacing and low cost. In this paper, two imaging regimes, namely, MIMO-planar scanning and MIMO cylindrical scanning, are described in terms of signal models, imaging algorithms, experimental systems, and imaging results. The results show the great application potential of the imaging technology in various scenarios.
20
2018, 7(5): 548-556.
Micromotion refers to the small and non-uniform motion of the target or several target components along the radar line of sight. Using the high-resolution three-Dimensional (3D) Inverse Synthetic Aperture Radar (ISAR) imaging, the structural information and motion status of micromotion targets can be obtained, providing essential features for the detection, tracking, identification, and classification, which play important roles in the space situation awareness and ballistic missile defense. Given the complex micromotion forms and the non-stationary radar echoes, the available parametric ISAR imaging methods are no longer applicable. To overcome this limitation, this study aims to propose a high-resolution 3D imaging method for micromotion targets based on the scattering center trajectory matrix decomposition. First, the Range Instantaneous Doppler (RID) image series is generated to extract the support region of scattering centers by the watershed method. Then, the scattering center association is achieved based on the minimum Euclidean distance criterion. Considering the insufficient accuracy in the instantaneous slant range estimation with limited range resolution, a method for refined estimation of the trajectory matrix based on the modern spectrum analysis is proposed. Finally, the high-resolution 3D imaging of the micromotion targets is obtained by the trajectory matrix decomposition with constraints. The simulation results have demonstrated that the proposed method could effectively obtain high-resolution 3D imaging of the targets in complex micromotions such as nutation.
Micromotion refers to the small and non-uniform motion of the target or several target components along the radar line of sight. Using the high-resolution three-Dimensional (3D) Inverse Synthetic Aperture Radar (ISAR) imaging, the structural information and motion status of micromotion targets can be obtained, providing essential features for the detection, tracking, identification, and classification, which play important roles in the space situation awareness and ballistic missile defense. Given the complex micromotion forms and the non-stationary radar echoes, the available parametric ISAR imaging methods are no longer applicable. To overcome this limitation, this study aims to propose a high-resolution 3D imaging method for micromotion targets based on the scattering center trajectory matrix decomposition. First, the Range Instantaneous Doppler (RID) image series is generated to extract the support region of scattering centers by the watershed method. Then, the scattering center association is achieved based on the minimum Euclidean distance criterion. Considering the insufficient accuracy in the instantaneous slant range estimation with limited range resolution, a method for refined estimation of the trajectory matrix based on the modern spectrum analysis is proposed. Finally, the high-resolution 3D imaging of the micromotion targets is obtained by the trajectory matrix decomposition with constraints. The simulation results have demonstrated that the proposed method could effectively obtain high-resolution 3D imaging of the targets in complex micromotions such as nutation.
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