Currently,the use of intelligent systems for the automatic recognition of targets in the fields of defence and military has increased significantly.The primary advantage of these systems is that they do not need human...Currently,the use of intelligent systems for the automatic recognition of targets in the fields of defence and military has increased significantly.The primary advantage of these systems is that they do not need human participation in target recognition processes.This paper uses the particle swarm optimization(PSO)algorithm to select the optimal features in the micro-Doppler signature of sonar targets.The microDoppler effect is referred to amplitude/phase modulation on the received signal by rotating parts of a target such as propellers.Since different targets'geometric and physical properties are not the same,their micro-Doppler signature is different.This Inconsistency can be considered a practical issue(especially in the frequency domain)for sonar target recognition.Despite using 128-point fast Fourier transform(FFT)for the feature extraction step,not all extracted features contain helpful information.As a result,PSO selects the most optimum and valuable features.To evaluate the micro-Doppler signature of sonar targets and the effect of feature selection on sonar target recognition,the simplest and most popular machine learning algorithm,k-nearest neighbor(k-NN),is used,which is called k-PSO in this paper because of the use of PSO for feature selection.The parameters measured are the correct recognition rate,reliability rate,and processing time.The simulation results show that k-PSO achieved a 100%correct recognition rate and reliability rate at 19.35 s when using simulated data at a 15 dB signal-tonoise ratio(SNR)angle of 40°.Also,for the experimental dataset obtained from the cavitation tunnel,the correct recognition rate is 98.26%,and the reliability rate is 99.69%at 18.46s.Therefore,the k-PSO has an encouraging performance in automatically recognizing sonar targets when using experimental datasets and for real-world use.展开更多
The recognition of human movements based on radar m-D(micro-Doppler) signatures attracts great interest in the field of radar research on automatic target recognition. Because there are multiple frequency components o...The recognition of human movements based on radar m-D(micro-Doppler) signatures attracts great interest in the field of radar research on automatic target recognition. Because there are multiple frequency components overlapping seriously in the radar echoes from walking humans, it is a very difficult work to recognize walking humans based on radar echoes. In this paper, a recognition method of walking humans based on radar m-D signatures is proposed. In this method, the m-D spectrum is generated by generalized S transform first,and then the entropy segmentation is used to segment the interesting region from the original spectrum. Next,the m-D features are extracted from the m-D region. Lastly, the support vector machine is used to recognize different walking human targets. The simulation experiments considering two factors of height and velocity are also conducted to test the performance of this proposed method.展开更多
A laser coherent detection system of 1550 nm wavelength was presented, and experimen- tal research on detecting micro-Doppler effect in a dynamic target was developed. In the study, the return signal in the time domai...A laser coherent detection system of 1550 nm wavelength was presented, and experimen- tal research on detecting micro-Doppler effect in a dynamic target was developed. In the study, the return signal in the time domain is decomposed into a set of components in different wavelet scales by multi-resolution wavelet analysis, and the components are associated with the vibrational motions in a target. Then micro-Doppler signatures are extracted by applying the reconstruction. During the course of the final data processing frequency analysis and time-frequency analysis are applied to analyze the vibrationM signals and estimate the motion parameters successfully. The experimental results indicate that the system can effectively detect micro-Doppler information in a moving target, and the tiny vibrational signatures also can be acquired effectively by wavelet multi-resolution analy- sis and time-frequency analysis.展开更多
In traditional inverse synthetic aperture radar （ISAR） imaging of moving targets with rotational parts, the micro-Doppler （m-D） effects caused by the rotational parts influence the quality of the radar images. Rec...In traditional inverse synthetic aperture radar （ISAR） imaging of moving targets with rotational parts, the micro-Doppler （m-D） effects caused by the rotational parts influence the quality of the radar images. Recently, L. Stankovic proposed an m-D removal method based on L-statistics, which has been proved effective and simple. The algorithm can extract the m-D effects according to different behaviors of signals induced by rotational parts and rigid bodies in time-frequency （T-F） domain. However, by removing m-D effects, some useful short time Fourier transform （STFT） samples of rigid bodies are also extracted, which induces the side lobe problem of rigid bodies. A parameter estimation method for rigid bodies after m-D removal is proposed, which can accurately re- cover rigid bodies and avoid the side lobe problem by only using m-D removal. Simulations are given to validate the effectiveness of the proposed method.展开更多
The rotating micro-motion parts produce micro-Doppler(m-D)effects which severely influence the quality of inverse synthetic aperture radar(ISAR)imaging for complex moving targets.Recently,a method based on short-time ...The rotating micro-motion parts produce micro-Doppler(m-D)effects which severely influence the quality of inverse synthetic aperture radar(ISAR)imaging for complex moving targets.Recently,a method based on short-time Fourier transform(STFT)and L-statistics to remove m-D effects is proposed,which can separate the rigid body parts from interferences introduced by rotating parts.However,during the procedure of removing m-D parts,the useful data of the rigid body parts are also removed together with the m-D interferences.After summing the rest STFT samples,the result will be affected.A novel method is proposed to recover the missing values of the rigid body parts by the particle swarm optimization(PSO)algorithm.For PSO,each particle corresponds to a possible phase estimation of the missing values.The best particle is selected which has the minimal energy of the side lobes according to the best fitness value of particles.The simulation and measured data results demonstrate the effectiveness of the proposed method.展开更多
To measure projectile attitude in space flight, based on continuous wave （CW） radar, a new micro-Doppler effect testing technique is developed in this paper. It also establishes radar testing model for attitude of f...To measure projectile attitude in space flight, based on continuous wave （CW） radar, a new micro-Doppler effect testing technique is developed in this paper. It also establishes radar testing model for attitude of flying projectile and resolve micro-Doppler effect of projectile motion attitude. By distinguishing and geting attitude parameters such as micro-motion period, this technique can in- tuitively estimate the flight stability of projectile, and the validity of this technique is proved accord- ing to flight tests.展开更多
We present a novel algorithm that can determine rotation-related parameters of a target using FMCW （frequency modulated continuous wave） radars, not utilizing inertia information of the target. More specifically, th...We present a novel algorithm that can determine rotation-related parameters of a target using FMCW （frequency modulated continuous wave） radars, not utilizing inertia information of the target. More specifically, the proposed algorithm estimates the angular velocity vector of a target as a function of time, as well as the distances of scattering points in the wing tip from the rotation axis, just by analyzing Doppler spectrograms obtained from three or more radars. The obtained parameter values will be useful to classify targets such as hostile warheads or missiles for real-time operation, or to analyze the trajectory of targets under test for the instrumentation radar operation. The proposed algorithm is based on the convex optimization to obtain the rotation-related parameters. The performance of the proposed algorithm is assessed through Monte Carlo simulations. Estimation performance of the proposed algorithm depends on the target and radar geometry and improves as the number of iterations of the convex optimization steps increases.展开更多
Angular glint is a significant electromagnetic （EM） scattering signature of extended radar targets. Based on the adaptive cross approximation （ACA） algorithm accelerated method of moments （MoM） and the plane inc...Angular glint is a significant electromagnetic （EM） scattering signature of extended radar targets. Based on the adaptive cross approximation （ACA） algorithm accelerated method of moments （MoM） and the plane incident wave assumption, the narrowband, wideband and newly developed high-resolution range profile （HRRP） based angular glint calculation formulations are derived and applied to arbitrarily shaped three-dimensional （3D） perfectly electrical y conducting （PEC） objects. In addition, the near-field angular glint is emphasized, which is of great importance for radarseeker applications. Furthermore, with the HRRP based angular glint, an approach to rigorously determine range resolution cel s which own relatively smal er angular glint is provided. Numerical results are presented with new findings to demonstrate the usefulness of the developed formulations.展开更多
A ten-month field research study was meticulously conducted at Robert Moses State Park (RMSP) on the south shore of Long Island, NY. The objective was to determine if aerial phenomena of an unknown nature exist over a...A ten-month field research study was meticulously conducted at Robert Moses State Park (RMSP) on the south shore of Long Island, NY. The objective was to determine if aerial phenomena of an unknown nature exist over a coastal location and to characterize their properties and behaviors. Primary and secondary field observation methods were utilized in this data-centric study. Forensic engineering principles and methodologies guided the study. The challenges set forward were object detection, observation, and characterization, where multispectral electro-optical devices and radar were employed due to limited visual acuity and intermittent presentation of the phenomena. The primary means of detection utilized a 3 cm X-band radar operating in two scan geometries, the X- and Y-axis. Multispectral electro-optical devices were utilized as a secondary means of detection and identification. Data was emphasized using HF and LF detectors and spectrum analyzers incorporating EM, ultrasonic, magnetic, and RF field transducers to record spectral data in these domains. Data collection concentrated on characterizing VIS, NIR, SWIR, LWIR, UVA, UVB, UVC, and the higher energy spectral range of ionizing radiation (alpha, beta, gamma, and X-ray) recorded by Geiger-Müller counters as well as special purpose semiconductor diode sensors.展开更多
文摘Currently,the use of intelligent systems for the automatic recognition of targets in the fields of defence and military has increased significantly.The primary advantage of these systems is that they do not need human participation in target recognition processes.This paper uses the particle swarm optimization(PSO)algorithm to select the optimal features in the micro-Doppler signature of sonar targets.The microDoppler effect is referred to amplitude/phase modulation on the received signal by rotating parts of a target such as propellers.Since different targets'geometric and physical properties are not the same,their micro-Doppler signature is different.This Inconsistency can be considered a practical issue(especially in the frequency domain)for sonar target recognition.Despite using 128-point fast Fourier transform(FFT)for the feature extraction step,not all extracted features contain helpful information.As a result,PSO selects the most optimum and valuable features.To evaluate the micro-Doppler signature of sonar targets and the effect of feature selection on sonar target recognition,the simplest and most popular machine learning algorithm,k-nearest neighbor(k-NN),is used,which is called k-PSO in this paper because of the use of PSO for feature selection.The parameters measured are the correct recognition rate,reliability rate,and processing time.The simulation results show that k-PSO achieved a 100%correct recognition rate and reliability rate at 19.35 s when using simulated data at a 15 dB signal-tonoise ratio(SNR)angle of 40°.Also,for the experimental dataset obtained from the cavitation tunnel,the correct recognition rate is 98.26%,and the reliability rate is 99.69%at 18.46s.Therefore,the k-PSO has an encouraging performance in automatically recognizing sonar targets when using experimental datasets and for real-world use.
基金supported by National Natural Science Foundation of China(Grant Nos.611711226120131861471019)
文摘The recognition of human movements based on radar m-D(micro-Doppler) signatures attracts great interest in the field of radar research on automatic target recognition. Because there are multiple frequency components overlapping seriously in the radar echoes from walking humans, it is a very difficult work to recognize walking humans based on radar echoes. In this paper, a recognition method of walking humans based on radar m-D signatures is proposed. In this method, the m-D spectrum is generated by generalized S transform first,and then the entropy segmentation is used to segment the interesting region from the original spectrum. Next,the m-D features are extracted from the m-D region. Lastly, the support vector machine is used to recognize different walking human targets. The simulation experiments considering two factors of height and velocity are also conducted to test the performance of this proposed method.
文摘A laser coherent detection system of 1550 nm wavelength was presented, and experimen- tal research on detecting micro-Doppler effect in a dynamic target was developed. In the study, the return signal in the time domain is decomposed into a set of components in different wavelet scales by multi-resolution wavelet analysis, and the components are associated with the vibrational motions in a target. Then micro-Doppler signatures are extracted by applying the reconstruction. During the course of the final data processing frequency analysis and time-frequency analysis are applied to analyze the vibrationM signals and estimate the motion parameters successfully. The experimental results indicate that the system can effectively detect micro-Doppler information in a moving target, and the tiny vibrational signatures also can be acquired effectively by wavelet multi-resolution analy- sis and time-frequency analysis.
基金supported by the National Natural Science Foundation of China(61471149)the Program for New Century Excellent Talents in University(NCET-12-0149)+2 种基金the National Science Foundation for Postdoctoral Scientists of China(2013M540292)the postdoctoral scienceresearch developmental foundation of Heilongjiang province(LBHQ11092)the Heilongjiang Postdoctoral Specialized Research Fund
文摘In traditional inverse synthetic aperture radar （ISAR） imaging of moving targets with rotational parts, the micro-Doppler （m-D） effects caused by the rotational parts influence the quality of the radar images. Recently, L. Stankovic proposed an m-D removal method based on L-statistics, which has been proved effective and simple. The algorithm can extract the m-D effects according to different behaviors of signals induced by rotational parts and rigid bodies in time-frequency （T-F） domain. However, by removing m-D effects, some useful short time Fourier transform （STFT） samples of rigid bodies are also extracted, which induces the side lobe problem of rigid bodies. A parameter estimation method for rigid bodies after m-D removal is proposed, which can accurately re- cover rigid bodies and avoid the side lobe problem by only using m-D removal. Simulations are given to validate the effectiveness of the proposed method.
基金the National Natural Science Foundation of China(61622107,61871146).
文摘The rotating micro-motion parts produce micro-Doppler(m-D)effects which severely influence the quality of inverse synthetic aperture radar(ISAR)imaging for complex moving targets.Recently,a method based on short-time Fourier transform(STFT)and L-statistics to remove m-D effects is proposed,which can separate the rigid body parts from interferences introduced by rotating parts.However,during the procedure of removing m-D parts,the useful data of the rigid body parts are also removed together with the m-D interferences.After summing the rest STFT samples,the result will be affected.A novel method is proposed to recover the missing values of the rigid body parts by the particle swarm optimization(PSO)algorithm.For PSO,each particle corresponds to a possible phase estimation of the missing values.The best particle is selected which has the minimal energy of the side lobes according to the best fitness value of particles.The simulation and measured data results demonstrate the effectiveness of the proposed method.
基金Supported by the National Natural Science Fundation of China(61174219)
文摘To measure projectile attitude in space flight, based on continuous wave （CW） radar, a new micro-Doppler effect testing technique is developed in this paper. It also establishes radar testing model for attitude of flying projectile and resolve micro-Doppler effect of projectile motion attitude. By distinguishing and geting attitude parameters such as micro-motion period, this technique can in- tuitively estimate the flight stability of projectile, and the validity of this technique is proved accord- ing to flight tests.
文摘We present a novel algorithm that can determine rotation-related parameters of a target using FMCW （frequency modulated continuous wave） radars, not utilizing inertia information of the target. More specifically, the proposed algorithm estimates the angular velocity vector of a target as a function of time, as well as the distances of scattering points in the wing tip from the rotation axis, just by analyzing Doppler spectrograms obtained from three or more radars. The obtained parameter values will be useful to classify targets such as hostile warheads or missiles for real-time operation, or to analyze the trajectory of targets under test for the instrumentation radar operation. The proposed algorithm is based on the convex optimization to obtain the rotation-related parameters. The performance of the proposed algorithm is assessed through Monte Carlo simulations. Estimation performance of the proposed algorithm depends on the target and radar geometry and improves as the number of iterations of the convex optimization steps increases.
文摘Angular glint is a significant electromagnetic （EM） scattering signature of extended radar targets. Based on the adaptive cross approximation （ACA） algorithm accelerated method of moments （MoM） and the plane incident wave assumption, the narrowband, wideband and newly developed high-resolution range profile （HRRP） based angular glint calculation formulations are derived and applied to arbitrarily shaped three-dimensional （3D） perfectly electrical y conducting （PEC） objects. In addition, the near-field angular glint is emphasized, which is of great importance for radarseeker applications. Furthermore, with the HRRP based angular glint, an approach to rigorously determine range resolution cel s which own relatively smal er angular glint is provided. Numerical results are presented with new findings to demonstrate the usefulness of the developed formulations.
文摘A ten-month field research study was meticulously conducted at Robert Moses State Park (RMSP) on the south shore of Long Island, NY. The objective was to determine if aerial phenomena of an unknown nature exist over a coastal location and to characterize their properties and behaviors. Primary and secondary field observation methods were utilized in this data-centric study. Forensic engineering principles and methodologies guided the study. The challenges set forward were object detection, observation, and characterization, where multispectral electro-optical devices and radar were employed due to limited visual acuity and intermittent presentation of the phenomena. The primary means of detection utilized a 3 cm X-band radar operating in two scan geometries, the X- and Y-axis. Multispectral electro-optical devices were utilized as a secondary means of detection and identification. Data was emphasized using HF and LF detectors and spectrum analyzers incorporating EM, ultrasonic, magnetic, and RF field transducers to record spectral data in these domains. Data collection concentrated on characterizing VIS, NIR, SWIR, LWIR, UVA, UVB, UVC, and the higher energy spectral range of ionizing radiation (alpha, beta, gamma, and X-ray) recorded by Geiger-Müller counters as well as special purpose semiconductor diode sensors.
