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1
2015, 4(4): 481-489.
Abstract
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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.
2
2015, 4(6): 658-665.
This paper presents a novel texture feature extraction method based on a Gabor filter and Three-Patch Local Binary Patterns (TPLBP) for Synthetic Aperture Rader (SAR) target recognition. First, SAR images are processed by a Gabor filter in different directions to enhance the significant features of the targets and their shadows. Then, the effective local texture features based on the Gabor filtered images are extracted by TPLBP. This not only overcomes the shortcoming of Local Binary Patterns (LBP), which cannot describe texture features for large scale neighborhoods, but also maintains the rotation invariant characteristic which alleviates the impact of the direction variations of SAR targets on recognition performance. Finally, we use an Extreme Learning Machine (ELM) classifier and extract the texture features. The experimental results of MSTAR database demonstrate the effectiveness of the proposed method.
This paper presents a novel texture feature extraction method based on a Gabor filter and Three-Patch Local Binary Patterns (TPLBP) for Synthetic Aperture Rader (SAR) target recognition. First, SAR images are processed by a Gabor filter in different directions to enhance the significant features of the targets and their shadows. Then, the effective local texture features based on the Gabor filtered images are extracted by TPLBP. This not only overcomes the shortcoming of Local Binary Patterns (LBP), which cannot describe texture features for large scale neighborhoods, but also maintains the rotation invariant characteristic which alleviates the impact of the direction variations of SAR targets on recognition performance. Finally, we use an Extreme Learning Machine (ELM) classifier and extract the texture features. The experimental results of MSTAR database demonstrate the effectiveness of the proposed method.
3
2015, 4(1): 107-121.
Synthetic Aperture Radar (SAR) is widely used in ship surveillance. High-Resolution Wide-Swath (HRWS) SAR data are simultaneously collected, which introduces challenges and offers new research opportunities. SAR-based ship-surveillance technologies and the performance requirements of SAR systems are reviewed and summarized. Furthermore, the characteristics of HRWS SAR imaging and ship surveillance technologies are considered in tandem, and preliminary research results on ship detection, feature extraction, and classification are discussed. Finally, we point out issues to be addressed in future work.
Synthetic Aperture Radar (SAR) is widely used in ship surveillance. High-Resolution Wide-Swath (HRWS) SAR data are simultaneously collected, which introduces challenges and offers new research opportunities. SAR-based ship-surveillance technologies and the performance requirements of SAR systems are reviewed and summarized. Furthermore, the characteristics of HRWS SAR imaging and ship surveillance technologies are considered in tandem, and preliminary research results on ship detection, feature extraction, and classification are discussed. Finally, we point out issues to be addressed in future work.
4
2015, 4(2): 230-239.
Video Synthetic Aperture Radar (ViSAR) system offers high imaging frame rate, and high resolution, and it is consequently used to investigate and locate near-moving targets. Compared with microwave SAR, the practical application of ViSAR is restricted by motion compensation caused by short wavelength. Even slight platform vibrations cause significant variations in the phase of echo signal.Thus, it is imperative to analyze the motion compensation and the error of ViSAR. In this study, the results show that imaging is affected less in the direction of flight direction and by low vibration in the direction of the slant range. In contrast, high-frequency vibration in the direction of the slant range requires higher compensation accuracy. Given the particularity of ViSAR's motion compensation, a compensation scheme is designed to achieve high compensation precision .The effectiveness of the scheme is verified by ViSAR imaging simulation experiments.
Video Synthetic Aperture Radar (ViSAR) system offers high imaging frame rate, and high resolution, and it is consequently used to investigate and locate near-moving targets. Compared with microwave SAR, the practical application of ViSAR is restricted by motion compensation caused by short wavelength. Even slight platform vibrations cause significant variations in the phase of echo signal.Thus, it is imperative to analyze the motion compensation and the error of ViSAR. In this study, the results show that imaging is affected less in the direction of flight direction and by low vibration in the direction of the slant range. In contrast, high-frequency vibration in the direction of the slant range requires higher compensation accuracy. Given the particularity of ViSAR's motion compensation, a compensation scheme is designed to achieve high compensation precision .The effectiveness of the scheme is verified by ViSAR imaging simulation experiments.
5
2015, 4(2): 123-129.
In modern high resolution SAR data, due to the intrinsic side-looking geometry of SAR sensors, layover and foreshortening issues inevitably arise, especially in dense urban areas. SAR tomography provides a new way of overcoming these problems by exploiting the back-scattering property for each pixel. However, traditional non-parametric spectral estimators, e.g. Truncated Singular Value Decomposition (TSVD), are limited by their poor elevation resolution, which is not comparable to the azimuth and slant-range resolution. In this paper, the Compressive Sensing (CS) approach using Basis Pursuit (BP) and TWo-step Iterative Shrinkage/Thresholding (TWIST) are introduced. Experimental studies with real spotlight-mode TerraSAR-X dataset are carried out using both BP and TWIST, to demonstrate the merits of compressive sensing approaches in terms of robustness, computational efficiency, and super-resolution capability.
In modern high resolution SAR data, due to the intrinsic side-looking geometry of SAR sensors, layover and foreshortening issues inevitably arise, especially in dense urban areas. SAR tomography provides a new way of overcoming these problems by exploiting the back-scattering property for each pixel. However, traditional non-parametric spectral estimators, e.g. Truncated Singular Value Decomposition (TSVD), are limited by their poor elevation resolution, which is not comparable to the azimuth and slant-range resolution. In this paper, the Compressive Sensing (CS) approach using Basis Pursuit (BP) and TWo-step Iterative Shrinkage/Thresholding (TWIST) are introduced. Experimental studies with real spotlight-mode TerraSAR-X dataset are carried out using both BP and TWIST, to demonstrate the merits of compressive sensing approaches in terms of robustness, computational efficiency, and super-resolution capability.
6
2015, 4(6): 630-638.
As one of the most useful phenomena for separating sea clutter and marine targets, micro-Doppler (m-D) describes the refined motion characteristics of a marine target and helps to improve the abilities of radar detection and recognition. In this study, based on maritime radar, the signal model of a target with micromotion in sea clutter is described. Initially, the definitions of micromotion and m-D are briefly reviewed with a description of their details, and a classification of rigid marine targets that exhibit micromotion is introduced. Then, according to the duration of the observation time, we establish two types of signal models, i.e., in one range unit and across range unit. According to the type of motion, we establish separate signal models for non-uniform translational motion and rotational motion. Finally, the properties of micromotion are analyzed using real radar data, and the effectiveness of the established models is verified.
As one of the most useful phenomena for separating sea clutter and marine targets, micro-Doppler (m-D) describes the refined motion characteristics of a marine target and helps to improve the abilities of radar detection and recognition. In this study, based on maritime radar, the signal model of a target with micromotion in sea clutter is described. Initially, the definitions of micromotion and m-D are briefly reviewed with a description of their details, and a classification of rigid marine targets that exhibit micromotion is introduced. Then, according to the duration of the observation time, we establish two types of signal models, i.e., in one range unit and across range unit. According to the type of motion, we establish separate signal models for non-uniform translational motion and rotational motion. Finally, the properties of micromotion are analyzed using real radar data, and the effectiveness of the established models is verified.
7
2015, 4(6): 621-629.
This paper reports the classification of helicopters, propeller-driven aircraft, and turbojet based on differences in their time-domain modulation periods using a conventional radar system. First, we determine the modulation periods of their time-domain echoes. Then, based on the differences in the time-domain modulation periods, we propose a method for the extraction of time-domain correlation features. Finally, based on the simulated and measured data, via a support vector machine classifier, it is proved that the time-domain correlation features can yield the good classification performance, even with the relatively low pulse repetition frequency, which may induce the ambiguity in Doppler-frequency domain.
This paper reports the classification of helicopters, propeller-driven aircraft, and turbojet based on differences in their time-domain modulation periods using a conventional radar system. First, we determine the modulation periods of their time-domain echoes. Then, based on the differences in the time-domain modulation periods, we propose a method for the extraction of time-domain correlation features. Finally, based on the simulated and measured data, via a support vector machine classifier, it is proved that the time-domain correlation features can yield the good classification performance, even with the relatively low pulse repetition frequency, which may induce the ambiguity in Doppler-frequency domain.
8
2015, 4(1): 93-98.
In this study, we propose a new semi-supervised classification method for Polarimetric SAR (PolSAR) images, aiming at handling the issue that the number of train set is small. First, considering the scattering characters of PolSAR data, this method extracts multiple scattering features using target decomposition approach. Then, a semi-supervised learning model is established based on a co-training framework and Support Vector Machine (SVM). Both labeled and unlabeled data are utilized in this model to obtain high classification accuracy. Third, a recovery scheme based on the Wishart classifier is proposed to improve the classification performance. From the experiments conducted in this study, it is evident that the proposed method performs more effectively compared with other traditional methods when the number of train set is small.
In this study, we propose a new semi-supervised classification method for Polarimetric SAR (PolSAR) images, aiming at handling the issue that the number of train set is small. First, considering the scattering characters of PolSAR data, this method extracts multiple scattering features using target decomposition approach. Then, a semi-supervised learning model is established based on a co-training framework and Support Vector Machine (SVM). Both labeled and unlabeled data are utilized in this model to obtain high classification accuracy. Third, a recovery scheme based on the Wishart classifier is proposed to improve the classification performance. From the experiments conducted in this study, it is evident that the proposed method performs more effectively compared with other traditional methods when the number of train set is small.
9
2015, 4(6): 609-620.
This study examines the complexities of using netted radar to recognize and resolve ballistic midcourse targets. The application of micro-motion feature extraction to ballistic mid-course targets is analyzed, and the current status of application and research on micro-motion feature recognition is concluded for singlefunction radar networks such as low- and high-resolution imaging radar networks. Advantages and disadvantages of these networks are discussed with respect to target recognition. Hybrid-mode radar networks combine low- and high-resolution imaging radar and provide a specific reference frequency that is the basis for ballistic target recognition. Main research trends are discussed for hybrid-mode networks that apply micromotion feature extraction to ballistic mid-course targets.
This study examines the complexities of using netted radar to recognize and resolve ballistic midcourse targets. The application of micro-motion feature extraction to ballistic mid-course targets is analyzed, and the current status of application and research on micro-motion feature recognition is concluded for singlefunction radar networks such as low- and high-resolution imaging radar networks. Advantages and disadvantages of these networks are discussed with respect to target recognition. Hybrid-mode radar networks combine low- and high-resolution imaging radar and provide a specific reference frequency that is the basis for ballistic target recognition. Main research trends are discussed for hybrid-mode networks that apply micromotion feature extraction to ballistic mid-course targets.
10
2015, 4(3): 351-360.
Aiming at meeting the requirement of the amass high-quality SAR images needed by template-based ground target recognition engineering practice, a novel efficient SAR signal level simulation method is proposed. The electromagnetic scattering interaction mechanisms including coherent clutter of ground, multiple reflection and edge diffraction of vehicle, coupling-scattering between vehicle and ground are accurately estimated by utilizing an efficient ray-tracing technique. High quality SAR images are finally created through the SAR imaging procedure. Simulation results show that, the new method is feasible and effective.
Aiming at meeting the requirement of the amass high-quality SAR images needed by template-based ground target recognition engineering practice, a novel efficient SAR signal level simulation method is proposed. The electromagnetic scattering interaction mechanisms including coherent clutter of ground, multiple reflection and edge diffraction of vehicle, coupling-scattering between vehicle and ground are accurately estimated by utilizing an efficient ray-tracing technique. High quality SAR images are finally created through the SAR imaging procedure. Simulation results show that, the new method is feasible and effective.
11
2015, 4(5): 527-537.
This paper presents the design of a handheld pseudo random coded Ultra-WideBand (UWB) radar for human sensing. The main tasks of the radar are to track the moving human object and extract the human respiratory frequency. In order to achieve perfect penetrability and good range resolution, m sequence with a carrier of 800 MHz is chosen as the transmitting signal. The modulated m-sequence can be generated directly by the high-speed DAC and FPGA to reduce the size of the radar system, and the mean power of the transmitting signal is 5 dBm. The receiver has two receiving channels based on hybrid sampling, the first receiving channel is to sample the reference signal and the second receiving channel is to obtain the radar echo. The real-time pulse compression is computed in parallel with a group of on-chip DSP48E slices in FPGA to improve the scanning rate of the radar system. Additionally, the algorithms of moving target tracking and life detection are implemented using Intels micro-processor, and the detection results are sent to the micro displayer fixed on the helmet. The experimental results show that the moving target located at less than 16 m far away from the wall can be tracked, and the respiratory frequency of the static human at less than 14 m far away from the wall can be extracted.
This paper presents the design of a handheld pseudo random coded Ultra-WideBand (UWB) radar for human sensing. The main tasks of the radar are to track the moving human object and extract the human respiratory frequency. In order to achieve perfect penetrability and good range resolution, m sequence with a carrier of 800 MHz is chosen as the transmitting signal. The modulated m-sequence can be generated directly by the high-speed DAC and FPGA to reduce the size of the radar system, and the mean power of the transmitting signal is 5 dBm. The receiver has two receiving channels based on hybrid sampling, the first receiving channel is to sample the reference signal and the second receiving channel is to obtain the radar echo. The real-time pulse compression is computed in parallel with a group of on-chip DSP48E slices in FPGA to improve the scanning rate of the radar system. Additionally, the algorithms of moving target tracking and life detection are implemented using Intels micro-processor, and the detection results are sent to the micro displayer fixed on the helmet. The experimental results show that the moving target located at less than 16 m far away from the wall can be tracked, and the respiratory frequency of the static human at less than 14 m far away from the wall can be extracted.
12
2015, 4(3): 301-308.
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.
13
2015, 4(2): 136-148.
Multiple-Input Multiple-Output (MIMO) radar is an emerging radar system that is of great interest to military and academic organizations due to its advantages and extensive applications. The main purpose of Space-Time Adaptive Processing (STAP) is to suppress ground clutter and realize Ground Moving Target Indication (GMTI). Nowadays, STAP technology has been extended to MIMO radar systems, and MIMO radar STAP has quickly become a hot research topic in international radar fields. This paper provides a detailed description of the extension and significant meaning of MIMO-STAP, and gives an overview of the current research status of clutter modeling, analysis of clutter Degree Of Freedom (DOF), reduced-dimension (reduced-rank) processing, simultaneous suppression of clutter plus jamming, non-homogeneous environment processing, and so on. The future perspective for the development of MIMO-STAP technology is also discussed.
Multiple-Input Multiple-Output (MIMO) radar is an emerging radar system that is of great interest to military and academic organizations due to its advantages and extensive applications. The main purpose of Space-Time Adaptive Processing (STAP) is to suppress ground clutter and realize Ground Moving Target Indication (GMTI). Nowadays, STAP technology has been extended to MIMO radar systems, and MIMO radar STAP has quickly become a hot research topic in international radar fields. This paper provides a detailed description of the extension and significant meaning of MIMO-STAP, and gives an overview of the current research status of clutter modeling, analysis of clutter Degree Of Freedom (DOF), reduced-dimension (reduced-rank) processing, simultaneous suppression of clutter plus jamming, non-homogeneous environment processing, and so on. The future perspective for the development of MIMO-STAP technology is also discussed.
14
2015, 4(3): 241-253.
The concept of Geosynchronous Circular SAR (Geo-CSAR) is introduced in this paper. With the design of the geosynchronous orbit parameters, a near-circular satellite sub-track could be formed to enable the staring imaging mode, which supports the advanced applications for wide-field and 3-D information acquisition under long-term consistent observation. This paper also analyzes Geo-CSAR's imaging formation capabilities, and concludes its attractive advantages over low-earth orbit spaceborne SAR in terms of instantaneous coverage, consistent observing area, 3-D positioning accuracy and etc.. Encouraging expectations for Geo-CSAR thus could be positively predicted in military investigation and disaster monitoring management applications.
The concept of Geosynchronous Circular SAR (Geo-CSAR) is introduced in this paper. With the design of the geosynchronous orbit parameters, a near-circular satellite sub-track could be formed to enable the staring imaging mode, which supports the advanced applications for wide-field and 3-D information acquisition under long-term consistent observation. This paper also analyzes Geo-CSAR's imaging formation capabilities, and concludes its attractive advantages over low-earth orbit spaceborne SAR in terms of instantaneous coverage, consistent observing area, 3-D positioning accuracy and etc.. Encouraging expectations for Geo-CSAR thus could be positively predicted in military investigation and disaster monitoring management applications.
15
2015, 4(5): 600-607.
The Phase Gradient Autofocus (PGA) algorithm can remove the high order phase error effectively, which is of great significance to get high resolution images in real-time processing. While PGA usually needs iteration, which necessitates long working hours. In addition, the performances of the algorithm are not stable in different scene applications. This severely constrains the application of PGA in real-time processing. Isolated scatter selection and windowing are two important algorithmic steps of Phase Gradient Autofocus Algorithm. Therefore, this paper presents an isolated scatter selection method based on sample mean and a windowing method based on pulse envelope. These two methods are highly adaptable to data, which would make the algorithm obtain better stability and need less iteration. The adaptability of the improved PGA is demonstrated with the experimental results of real radar data.
The Phase Gradient Autofocus (PGA) algorithm can remove the high order phase error effectively, which is of great significance to get high resolution images in real-time processing. While PGA usually needs iteration, which necessitates long working hours. In addition, the performances of the algorithm are not stable in different scene applications. This severely constrains the application of PGA in real-time processing. Isolated scatter selection and windowing are two important algorithmic steps of Phase Gradient Autofocus Algorithm. Therefore, this paper presents an isolated scatter selection method based on sample mean and a windowing method based on pulse envelope. These two methods are highly adaptable to data, which would make the algorithm obtain better stability and need less iteration. The adaptability of the improved PGA is demonstrated with the experimental results of real radar data.
16
2015, 4(4): 445-451.
Because of the limitations of traditional Principal Component Analysis (PCA) in clutter reduction, an improved PCA subspace method is proposed based on the 2D wavelet transform. Moreover, the combination of the improved subspace method and adaptive filtering ensures the signal fidelity and learning adaptability of adaptive filtering. Then, an adaptive clutter reduction algorithm based on wavelet transform and PCA, as well as adaptive filtering, is proposed. The experimental results suggest that the proposed method improves the signal to clutter ratio and target image definition.
Because of the limitations of traditional Principal Component Analysis (PCA) in clutter reduction, an improved PCA subspace method is proposed based on the 2D wavelet transform. Moreover, the combination of the improved subspace method and adaptive filtering ensures the signal fidelity and learning adaptability of adaptive filtering. Then, an adaptive clutter reduction algorithm based on wavelet transform and PCA, as well as adaptive filtering, is proposed. The experimental results suggest that the proposed method improves the signal to clutter ratio and target image definition.
17
2015, 4(3): 334-342.
In case of high-resolution, low grazing angle, high sea state, and horizontal transmitting, horizontal receiving polarization, the radar returns are strengthened, resulting in sea spikes. The sea spikes have the characteristics of high amplitudes, nonstationary, and non-Gaussian, which have a strong impact on the radar detection of weak marine moving targets. This study proposes a method for sea clutter suppression. Firstly, based on the sea spikes identification and selection method, the amplitude, temporal correlation, Doppler spectrum, and fractional power spectrum properties of sea spikes are analyzed. Secondly, the data to be detected are chosen by selecting the background clutter with minimum mean power, which can also eliminate the sea spikes. Correspondingly, sea clutter is suppressed with improved Signal-to-Clutter Ratio (SCR). Finally, the results of experiment with real radar data verify the effectiveness of the proposed method.
In case of high-resolution, low grazing angle, high sea state, and horizontal transmitting, horizontal receiving polarization, the radar returns are strengthened, resulting in sea spikes. The sea spikes have the characteristics of high amplitudes, nonstationary, and non-Gaussian, which have a strong impact on the radar detection of weak marine moving targets. This study proposes a method for sea clutter suppression. Firstly, based on the sea spikes identification and selection method, the amplitude, temporal correlation, Doppler spectrum, and fractional power spectrum properties of sea spikes are analyzed. Secondly, the data to be detected are chosen by selecting the background clutter with minimum mean power, which can also eliminate the sea spikes. Correspondingly, sea clutter is suppressed with improved Signal-to-Clutter Ratio (SCR). Finally, the results of experiment with real radar data verify the effectiveness of the proposed method.
18
2015, 4(2): 222-229.
This study uses time domain terahertz radar system to discuss systematic imaging studies on the scaled models based on the improved Back-Projection(BP) algorithm. We image the scaled models with different shapes and are able to distinguish spatial gaps as small as 6 mm. TheTheoretical calculation predicts that the lateral resolution and the axial resolution can be as high as 0.125 mm. Center enhancement and background rings caused by the algorithm in the imaging results are also qualitatively analyzed and are proposed methods to overcome this problem.
This study uses time domain terahertz radar system to discuss systematic imaging studies on the scaled models based on the improved Back-Projection(BP) algorithm. We image the scaled models with different shapes and are able to distinguish spatial gaps as small as 6 mm. TheTheoretical calculation predicts that the lateral resolution and the axial resolution can be as high as 0.125 mm. Center enhancement and background rings caused by the algorithm in the imaging results are also qualitatively analyzed and are proposed methods to overcome this problem.
19
2015, 4(1): 11-19.
This study proposes a novel Multiple Input Multiple Output (MIMO) microwave imaging mode based on arc antenna array, which is mounted on the belly of platform. In this mode, an arc aperture is quickly synthesized using an MIMO. Consequently, high space and time resolution images of the illuminated scene around the platform are acquired. First, an imaging principle model based on arc antenna array is described, and its signal model is developed. Then, an imaging algorithm based on confocal projection is discussed and the performance of the mode is analyzed. Finally, the feasibility of the imaging mode and the validity of the proposed algorithm are demonstrated with a numerical simulation.
This study proposes a novel Multiple Input Multiple Output (MIMO) microwave imaging mode based on arc antenna array, which is mounted on the belly of platform. In this mode, an arc aperture is quickly synthesized using an MIMO. Consequently, high space and time resolution images of the illuminated scene around the platform are acquired. First, an imaging principle model based on arc antenna array is described, and its signal model is developed. Then, an imaging algorithm based on confocal projection is discussed and the performance of the mode is analyzed. Finally, the feasibility of the imaging mode and the validity of the proposed algorithm are demonstrated with a numerical simulation.
20
2015, 4(2): 172-177.
A new method of Radar Cross Section (RCS) measurement based on near-field imaging of cylindrical scanning surface is proposed. The method is based on the core assumption that the target consists of ideal isotropic scattered centers. Three-dimensional radar scattered images are obtained by using the proposed method, and then to obtain the RCS of the target, the scattered far field is calculated by summing the fields generated by the equivalent scattered centers. Not only three dimensional radar reflectivity images but also the RCS of targets in certain three dimensional angle areas can be obtained. Compared with circular scanning that can only obtain twodimensional radar reflectivity images and RCS results in two-dimensional angle areas, cylindrical scanning can provide more information about the scattering properties of the targets. The method has strong practicability and its validity is verified by simulations.
A new method of Radar Cross Section (RCS) measurement based on near-field imaging of cylindrical scanning surface is proposed. The method is based on the core assumption that the target consists of ideal isotropic scattered centers. Three-dimensional radar scattered images are obtained by using the proposed method, and then to obtain the RCS of the target, the scattered far field is calculated by summing the fields generated by the equivalent scattered centers. Not only three dimensional radar reflectivity images but also the RCS of targets in certain three dimensional angle areas can be obtained. Compared with circular scanning that can only obtain twodimensional radar reflectivity images and RCS results in two-dimensional angle areas, cylindrical scanning can provide more information about the scattering properties of the targets. The method has strong practicability and its validity is verified by simulations.
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