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Two-dimensional near-field multiple signal classification algorithm-based impact localization

JOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES 2015年第4期26卷 400-413页

作者： Yuan, Shenfang Zhong, Yongteng Qiu, Lei Wang, Zhiling Nanjing Univ Aeronaut & Astronaut State Key Lab Mech & Control Mech Struct Nanjing 210016 Peoples R China

The susceptibility of composite materials to internal damage caused by low-velocity impact is well known and creates a major concern related to structural health monitoring. This research presents a near-field impact monitoring method based on the two-dimensional multiple signal classification method for the composite structure. Since elastic waves attenuate quickly in the complex aircraft composite structures and impacts may happen near the sensors, near-field impact monitoring method is important. However, most of the methods reported are based on the far-field assumption. When impacts occur not far enough from the sensors, this belongs to the near-field situation, where the elastic wave fronts are spherical and the direction estimation method with the plane wave hypothesis is no longer valid. Hence, this article focuses the research of a near-field multiple signal classification-based impact localization method. To verify the proposed method, two experiments are performed on composite structures. The localization results are in good agreement with the actual impact occurring positions in near-field area. Finally, the proposed method is applied to a real aircraft composite oil tank showing its successful performance on complex composite structure.

关键词： Impact monitoring multiple signal classification algorithm near-field composite structure

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Radar target classification method with reduced aspect dependency and improved noise performance using multiple signal classification algorithm

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IET RADAR SONAR AND NAVIGATION 2009年第6期3卷 583-595页

作者： Secmen, M. Turhan-Sayan, G. Middle E Tech Univ Dept Elect & Elect Engn TR-06531 Ankara Turkey

This study introduces a novel aspect and polarisation invariant radar target classification method based on the use of multiple signal classification (MUSIC) algorithm for feature extraction. In the suggested method, for each candidate target at each designated reference aspect, feature matrices called 'MUSIC spectrum matrices (MSMs)' are constructed using the target's scattered data at different late-time intervals. An individual MSM corresponds to a map of a target's natural resonance-related power distribution over the complex frequency plane under the chosen aspect angle/late-time interval conditions. The collection of these feature matrices is used first to determine the best late-time interval for optimal feature extraction. Then, the MSM of a target, which are computed over the optimal time interval at all reference aspects, are superposed to obtain the 'fused MUSIC spectrum matrix (FMSM)'. The FMSM of a target is its main classifier feature in the proposed method as the aspect dependency of an FMSM is highly reduced because of its multi-aspect construction process. The suggested method is demonstrated for both simple and complex target geometries such as conducting spheres, dielectric spheres and small-scale aircraft targets with high accuracy rates even for low SNR values using feature fusion at only a few different reference aspects.

关键词： radar signal processing Radar theory noise performance feature matrix MUSIC algorithm optimal feature extraction radar target recognition signal processing and detection resonance-related power distribution late-time interval condition target geometry electromagnetic wave polarisation matrix algebra feature extraction Algebra Combinatorial mathematics complex frequency plane multiaspect construction process fused MUSIC spectrum matrix dielectric sphere conducting sphere multiple signal classification algorithm polarisation-invariant radar target classification method geometry SNR value radar theory sensor fusion aspect dependency MSM signal classification small-scale aircraft target

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Analysis of magnetic source localization of P300 using the multiple signal classification algorithm

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PSYCHIATRY AND CLINICAL NEUROSCIENCES 2006年第6期60卷 645-651页

作者： Uohashi, Tetsuo Kitamura, Yoshihiro Ishizu, Suguru Okamoto, Motoi Yamada, Norihito Kuroda, Shigetoshi Okayama Univ Sch Med Dept Neuropsychiat Okayama 7008558 Japan Okayama Ryogo Ctr Okayama Japan Okayama Prefectural Hosp Okayama Japan Okayama Univ Sch Hlth Sci Okayama 7008530 Japan

The authors studied the localization of P300 magnetic sources using the multiple signal classification (MUSIC) algorithm. Six healthy subjects (aged 24-34 years old) were investigated with 148-channel whole-head type magnetencephalography using an auditory oddball paradigm in passive mode. The authors also compared six stimulus combinations in order to find the optimal stimulus parameters for P300 magnetic field (P300m) in passive mode. Bilateral MUSIC peaks were located on the mesial temporal, superior temporal and parietal lobes. Interestingly, all MUSIC peaks in these regions emerged earlier in the right hemisphere than in the left hemisphere, suggesting that the right hemisphere has predominance over the left in the processing activity associated with P300m. There were no significant differences among the six stimulus combinations in evoking those P300m sources. The results of the present study suggest that the MUSIC algorithm could be a useful tool for analysis of the time-course of P300m.

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Application of multiple signal classification algorithm to Frequency Estimation in Coherent Dual-Frequency Lidar

Application of Multiple Signal Classification Algorithm to F...

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International Conference on Optical Instruments and Technology (OIT) / 6th Conference on Advanced Laser Technology and Applications (ALTA)

作者： Li, Ruixiao Li, Kun Zhao, Changming Beijing Inst Technol Sch Optoelect Beijing 100081 Peoples R China Beijing Inst Satellite Informat Engn State Key Lab Space Ground Integrated Informat Te Beijing 100029 Peoples R China

ISBN: (数字)9781510617506

ISBN: (纸本)9781510617506;9781510617490

Coherent dual-frequency Lidar (CDFL) is a new development of Lidar which dramatically enhances the ability to decrease the influence of atmospheric interference by using dual-frequency laser to measure the range and velocity with high precision. Based on the nature of CDFL signals, we propose to apply the multiple signal classification (MUSIC) algorithm in place of the fast Fourier transform (FFT) to estimate the phase differences in dual-frequency Lidar. In the presence of Gaussian white noise, the simulation results show that the signal peaks are more evident when using MUSIC algorithm instead of FFT in condition of low signal-noise-ratio (SNR), which helps to improve the precision of detection on range and velocity, especially for the long distance measurement systems.

关键词： Coherent dual-frequency Lidar multiple signal classification algorithm signal-to-noise ratio

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Low-Frequency Ultrasound Thoracic signal Processing Based on Music algorithm and EMD Wavelet Thresholding

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IEEE ACCESS 2023年 11卷 73912-73921页

作者： Zhou, Yinggang Li, Jifeng Yan, Hua Yan, Xin Shenyang Univ Technol Sch Informat Sci & Engn Shenyang 110870 Peoples R China

Ultrasound is widely used in biomedical imaging. High-frequency ultrasound at MHz is usually used for good resolution. However, ultrasound at this band cannot permeate human thorax, for it is strongly scattered and reflected by air inclusions in the thorax. Low-frequency ultrasound can bypass this limitation and capture useful information deep within the thorax. Hence, this paper presents a new signal processing method to enhance the signal quality of low-frequency ultrasound imaging by improving the signal-to-noise ratio (SNR) and reducing the mean square error (MSE). Specifically, we propose a solution that integrates the empirical mode decomposition (EMD)-based wavelet thresholding algorithm with the multiple signal classification (MUSIC) algorithm. The MUSIC algorithm pre-processes the low-frequency ultrasound signal prior to implementing the EMD-based wavelet threshold denoising algorithm for further noise reduction. We assess the effectiveness of our approach through simulation and experimental research. Results demonstrate substantial performance improvements in the quality of low-frequency ultrasound signals with SNR enhancement ranging from 2.2915 to 3.3358 dB in the simulation, and MSE decrease of 0.3018. Moreover, the experiment yields an SNR improvement range of 1.0274 to 2.9372 dB and a corresponding decrease of 0.2202 in MSE. In agreement with the simulation outcomes, these results confirm the efficacy of our proposed method as an efficient solution for improving the quality of low-frequency ultrasound signals.

关键词： Low-frequency ultrasound transmissive thorax ultrasound multiple signal classification algorithm EMD-based wavelet threshold

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Generalised two stage cumulants-based MUSIC algorithm for passive mixed sources localisation

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IET signal PROCESSING 2019年第4期13卷 409-414页

作者： Ebrahimi, Ali Akbar Abutalebi, Hamid Reza Karimi, Mahmood Yazd Univ Elect Engn Dept Yazd Iran Shiraz Univ Sch Elect & Comp Engn Shiraz Iran

In this study, the authors address the problem of passive mixed near-field and far-field sources localisation using a uniform linear array (ULA) in which the signals received by the array may come from mixed sources. This study presents a new two stage cumulant-based multiple signal classification (MUSIC) algorithm for passive source localisation using fourth-order cumulants of a ULA data. The significant characteristic of the proposed algorithm is that it constructs a new special cumulant matrix to acquire more information of signals received by a ULA. Consequently, the proposed algorithm gives high direction of arrival (DOA) and range estimation accuracy, and alleviates the array aperture loss. Monte Carlo simulations are established to verify the effectiveness of the proposed method in increasing direction of arrival and range estimation accuracies.

关键词： direction-of-arrival estimation array signal processing Monte Carlo methods higher order statistics signal classification far-field sources uniform linear array passive source localisation fourth-order cumulants ULA data special cumulant matrix range estimation accuracy array aperture loss generalised two stage cumulants-based MUSIC algorithm passive mixed sources localisation near-field sources multiple signal classification algorithm direction of arrival DOA Monte Carlo simulations

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Joint estimation of DOA and polarisation for radar signals based on dual-polarised antenna array

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IET MICROWAVES ANTENNAS & PROPAGATION 2020年第10期14卷 989-998页

作者： Wu, Jian Zhu, Xiaojin He, Xiaoming Gao, Zhiyuan Fang, Yubin Shanghai Univ Sch Mechatron Engn & Automat Shanghai 200072 Peoples R China Shanghai Microwave Equipment Res Inst Shanghai 201802 Peoples R China

To apply polarisation information of radar signal in radar reconnaissance equipment, a joint estimation algorithm of the radar signal direction of arrival (DOA) and polarisation parameters based on dual-polarisation antenna array has been researched in this study. The mathematical model of dual-polarised circular array has been given, and the joint estimation method of DOA and polarisation parameters for radar signal based on multiple signal classification (MUSIC) algorithm has been analysed. To overcome the shortcomings such as high calculation cost for the MUSIC algorithm, the DOA-matrix algorithm has been presented. DOA-matrix algorithm can effectively distinguish the radar signals with different polarisation states in the same direction by use of eigen-decomposition of the DOA-matrix. Through matrix correlation calculation, spectral peak search has been avoided, and the computational cost and algorithm complexity are greatly reduced. Finally, the feasibility of the DOA-matrix algorithm has been simulated and analysed. The simulation results show that the DOA-matrix algorithm can effectively complete the joint estimation of DOA and polarisation parameters for radar signal. The running time reaches millisecond level, which has a strong application value in engineering.

关键词： array signal processing radar signal processing matrix algebra antenna arrays direction-of-arrival estimation polarisation signal classification DOA-matrix algorithm different polarisation states computational cost algorithm complexity polarisation parameters dual-polarised antenna array polarisation information radar reconnaissance equipment joint estimation algorithm radar signal direction dual-polarisation antenna array dual-polarised circular array joint estimation method multiple signal classification algorithm MUSIC algorithm

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Subspace-based super-resolution algorithm for ground moving target imaging and motion parameter estimation

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IET RADAR SONAR AND NAVIGATION 2016年第3期10卷 488-499页

作者： Ma, Jingtao Tao, Haihong Huang, Penghui Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Shaanxi Peoples R China

For synthetic aperture radar (SAR), most conventional algorithms provide a good performance in ground moving target imaging based on Fourier transform (FT). However, when multiple moving targets with the close centres exist, the conventional algorithms may suffer from the performance degradation since the spectra resolution of FT may be limited by the time samples. To address this issue, a super-resolution motion parameter estimation algorithm is proposed in this study. First, Keystone transform is applied to correct the linear range walk. Then the range curvature is compensated by the matched function with respect to the platform velocity. After performing the compensation of linear range walk and range curvature, the energy of a ground moving target is focused on one range cell, and then a first-order discrete polynomial-phase transform is applied to transform the quadratic phase signal into a single tone. After applying the smoothing technique to construct the covariance matrix of full rank, the multiple signal classification algorithm is utilised to estimate the target cross- and along-track velocities, which can significantly improve the motion parameter resolution performance compared with the FFT-based algorithms. The real SAR data processing results are used to validate the effectiveness and feasibility of the proposed algorithm.

关键词： radar resolution radar imaging synthetic aperture radar signal classification polynomials covariance matrices Fourier transforms subspace-based super-resolution algorithm ground moving target imaging motion parameter estimation synthetic aperture radar Fourier transform super-resolution motion parameter estimation algorithm linear range walk range curvature first-order discrete polynomial-phase transform quadratic phase signal multiple signal classification algorithm covariance matrix FFT-based algorithms

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A Novel Weak signal Detection Method via Chaotic Synchronization Using Chua's Circuit

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2017年第3期64卷 2255-2265页

作者： Li, Guozheng Zhang, Bo South China Univ Technol Sch Elect Power Guangzhou 510640 Peoples R China Beijing Jiaotong Univ Detect Techniques & Instrumentat Beijing Peoples R China Beijing Jiaotong Univ Sch Mech Safety Technol & Engn Beijing Peoples R China South China Univ Technol Sch Elect Power Guangzhou Peoples R China Zhejiang Univ Hangzhou Zhejiang Peoples R China Southwest Jiaotong Univ Chengdu Peoples R China Nanjing Univ Aeronaut & Astronaut Nanjing Peoples R China South China Univ Technol Sch Elect Power Guangzhou Peoples R China

This paper presents a novel detection method for weak sinusoidal signal embedded in strong noise. Two synchronization systems are constructed to implement this method, in which one is used to estimate the frequency and phase angle, the other is used to estimate the amplitude. The detection process is achieved in three steps. First, two synchronization systems are established based on chaotic synchronization theorem and adaptive algorithm. The test signal is injected into their driving ends. Second, in the first synchronization system, the frequency of the sinusoidal signal is obtained by the MUSIC algorithm. Then, the reference sinusoidal signal with this frequency can be generated and correlated with the test signal. The phase difference between them is obtained. Finally, in the second synchronization system, the amplitude of the reference signal is close to the actual amplitude of the sinusoidal signal in the process of synchronization. This detection system is achieved by the Chua's circuit, and its detection characteristics are verified by simulation and experimentation. The results show that it is feasible to obtain the parameters of the sinusoidal signal. It retains excellent detection performance, simplifies parameters setting, avoids the solution of the running state, and is easy to achieve.

关键词： Adaptive signal processing chaotic synchronization Chua's circuit multiple signal classification algorithm signal detection

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AC analysis of temperature effects on conversion efficiency of CuInGaSe₂ solar cells

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ELECTRONICS LETTERS 2015年第1期51卷 86-U103页

作者： Kim, Hong Tak Kim, Chang Duk Kim, Maeng Jun Sohn, Young-Soo Kyungpook Natl Univ Dept Phys Taegu 702701 South Korea Korea Atom Energy Res Inst Proton Engn Frontier Project Gyeongju 780904 South Korea Catholic Univ Daegu Gyongsan 712702 South Korea

The temperature effect on a CuInGaSe2 (CIGS) solar cell was investigated in the temperature range -10 to 80 degrees C using direct current (DC) and alternating current (AC) characteristic analysis of CIGS solar cells. The change rates of short-circuit current density (J(sc)), open-circuit voltage (V-oc), fill factor (FF) and efficiency (eta) with respect to temperature were investigated. In addition, the variation of impedance, total capacitance and dynamic resistance due to the temperature change implied that the width of the depletion region in a p-n junction shrank, and the effective minority carrier lifetime (tau(eff)) decreased. Consequently, J(sc) changed slightly due to the balance between the variation of the energy bandgap (E-g) and tau(eff). However, V-oc linearly decreased due to the relationship of E-g when the temperature increased. From these results, it has been concluded that V-oc plays an important role in the characteristics of the CIGS solar cell with change of temperature.

关键词： fluorescence Monte Carlo methods image classification optical microscopy fluorescence lifetime extraction algorithm multiple signal classification algorithm array signal processing direction-of-arrival estimations fluorescence lifetime imaging microscopy Monte Carlo simulations multiexponential decays

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