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orthogonal matching pursuit algorithm based on weighted cosine similarity for sound source localization

PHYSICA SCRIPTA 2023年第9期98卷 095020-095020页

作者： Xiao, Yue Wang, Junyu Yuan, Lei Nanchang Inst Technol Sch Mech Engn Nanchang 330099 Peoples R China

Compressive sensing overcomes the limitations of the Nyquist criteria and is one of the most widely used compressive sensing reconstruction algorithms. orthogonal matching pursuit (OMP) algorithm is simple, in terms of hardware implementation, and has high computational efficiency. However, the OMP algorithm exhibits poor identification performance for low-frequency sound sources and results in large localization deviations when the mesh spacing of the focus plane is small. In this study, a novel atom selection criterion based on weighted cosine similarity was proposed to improve the OMP algorithm for sound source localization and characterization. This method replaces the original inner product criterion to measure the correlation between the column vectors of the sensing matrix and the residuals, which addresses the atom selection error caused by the high correlation between atoms. Numerical simulations and experimental results show that the proposed method has a stronger anti-noise interference capability and higher accuracy for sound source identification with fewer sampling points, particularly in low-frequency and low signal-to-noise ratio environments. Compared to other OMP algorithms, the proposed method improves the performance of the OMP algorithm in sound source localization and widens the sound frequency range. This study is valuable for achieving highly accurate sound source localization and reducing measurement costs in practical applications.

关键词： compressive sensing orthogonal matching pursuit algorithm cosine similarity sound source localization

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An orthogonal matching pursuit algorithm Based on Singular Value Decomposition

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2020年第1期39卷 492-501页

作者： Zhang, Cui-juan Anqing Normal Univ Univ Key Lab Intelligent Percept & Comp Anhui Pro Sch Comp & Informat Anqing 246011 Peoples R China

A recovery algorithm is one of the most important components in compressive sensing. It is responsible for the recovery of sparse coefficients in some bases of the original signal from a set of non-adaptive and underdetermined linear measurements, and it is a key link between the front-end signal sensing system and back-end processing. In this study, an improved orthogonal matching pursuit algorithm based on singular value decomposition is proposed to overcome the limitations of existing algorithms, which effectively eliminates the correlation between the measured values. The results of simulation experiments show that the proposed algorithm significantly improves the average signal-to-noise ratio, and it performs more robustly than the classical orthogonal matching pursuit algorithm.

关键词： Compressive sensing Sparse prior Singular value decomposition orthogonal matching pursuit algorithm

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An Application of the orthogonal matching pursuit algorithm in Space-Time Adaptive Processing

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SENSORS 2020年第12期20卷 3468.-3468.页

作者： Slesicka, Anna Kawalec, Adam Mil Univ Technol Fac Elect Inst Radioelect Gen S Kaliskiego 2 PL-00908 Warsaw Poland

The article presents a new space-time adaptive processing (STAP) method for target detection in a heterogeneous and non-stationary environment. In study it was proven that it is possible to estimate the clutter covariance matrix (CCM) in STAP by using the MIMO (Multiple Input Multiple Output) radar geometry model and the orthogonal matching pursuit (OMP) algorithm. For the estimation of spatio-temporal spectrum of clutter and target, a model of joint sparse recovery was established. As a result, clutter suppression and target detection in a heterogeneous environment will be achieved. In addition, the proposed method uses a single snapshot of the radar data cube, which eliminates the need for access to all training cells.

关键词： space-time adaptive processing STAP sparse representation MIMO radar orthogonal matching pursuit algorithm clutter covariance matrix

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SENSITIVITY SIMULATION OF COMPRESSED SENSING BASED EW RECEIVER USING orthogonal matching pursuit algorithm

SENSITIVITY SIMULATION OF COMPRESSED SENSING BASED EW RECEIV...

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IEEE National Aerospace and Electronics Conference (NAECON)

作者： Liou, Lee L. Lin, David M. Lin, Ethan Chen, Chien-In H. US Air Force Res Lab Dayton OH 45431 USA Wright State Univ Dept Elect Engn Dayton OH 45435 USA

ISBN: (纸本)9781479946891

The wideband coverage of the traditional FFT-based electronic warfare (EW) receiver is limited by the sampling frequency of the analog-to-digital converter (ADC). Compressed sensing (CS) based wideband EW digital receiver has been proposed and under development to process wideband sparse signals with reduced sampling rate. In this study, we calculate the sensitivity of a CS based EW receiver. Two modulation schemes of CS are used. One is pseudorandom chip (PRC) and the other is non-uniform sampling (NUS) modulation. The orthogonal matching pursuit (OMP) algorithm is used to process CS data. The insufficient nature of the sparcity of the signal adversely affects the signal detection probability for both PRC and NUS modulation schemes. Methods to remedy this problem in both modulation schemes are proposed. The improvement in the signal detection and thus the sensitivity performance of the CS based receiver are presented.

关键词： analogue-digital conversion compressed sensing electronic warfare fast Fourier transforms signal detection ADC FFT-based electronic warfare receiver analog-to-digital converter nonuniform sampling modulation orthogonal matching pursuit algorithm pseudorandom chip sampling frequency sensitivity simulation signal detection probability wideband EW digital receiver wideband sparse signals Accuracy Frequency measurement matching pursuit algorithms Modulation Probability density function Receivers Sensitivity Compressed sensing electronic warfare matching pursuit algorithms analog digital converter signal acquisition Receivers Analog-digital conversion frequency measurement Fast Fourier transform Probability density function SAMPLING FREQUENCY AC to DC converters

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The Study on Fully Polarized Man-made Target One-dimensional Feature Extraction Based on orthogonal matching pursuit algorithm 9

The Study on Fully Polarized Man-made Target One-dimensional...

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2017 9th IEEE International Conference on Communication Software and Networks (ICCSN 2017)

作者： Hao Wu Dahai Dai Bin Liao Xuesong Wang College of Electronic Science and Engineering National University of Defense Technology

ISBN: (纸本)9781509038237;9781509038220

In radar imaging, the extraction of scattering centers is an extraordinary part of the target polarization feature study, and the research on one-dimensional range profile of radar is widely adopted for its simple implementation and short imaging time. In this paper, the study focuses on radar one-dimensional range profile, a novel polarized scattering center model based on orthogonal matching pursuit(OMP) algorithm is established, which is capable of estimating the position, intensity and the scattering verified by simulation and real missile data. matrix, and the effectiveness of the proposed method is

关键词： scattering center fully polarized one-dimensional range profile orthogonal matching pursuit algorithm

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Ultrasonic testing signal de-noising processing based on orthogonal matching pursuit algorithm

Ultrasonic testing signal de-noising processing based on ort...

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3rd International Conference on Applied Mechanics, Materials and Manufacturing (ICAMMM 2013)

作者： Yu, Yongfang Yi, Fei Cheng, Huanxin Cheng, Li ZheJiang Whyls Technol Co Ltd Hangzhou 310023 Zhejiang Peoples R China Qingdao Univ Sci & Technol Coll Automat & Elect Engn Qingdao 266042 Shandong Peoples R China Urumqi Xiaming Innovat Elect Technol Co Ltd Xinjiang 830011 Peoples R China

ISBN: (纸本)9783037858882

Ultrasonic NDT signal de-noising effect is the key indicators to determine whether the pipe is *** matching pursuit algorithm optimization process, the sampling signal and reconstructed signal by the method of least *** orthogonal matching pursuit algorithm for the sampling signal to optimize and reconstruct. It is successfully to verify the OMP algorithm can recover the signal based on the MATLAB *** a signal de-noising processing module to help staff to determine pipeline defects conveniently,it achieved de-noising successfully.

关键词： Ultrasonic testing orthogonal matching pursuit algorithm signal de-noising reconstructed waveform

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Damage identification of hinge joint in hollow slab bridge based on model updating and orthogonal matching pursuit algorithm

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MEASUREMENT 2024年 224卷

作者： Li, Shengli Yang, Haoxiang Guo, Pan Ren, Duochang Xu, Bin Liang, Zhenzhen Zhengzhou Univ Sch Civil Engn Zhengzhou 450001 Henan Peoples R China Henan Prov Engn Res Ctr Safety & Life Extens Prest Zhengzhou 450001 Henan Peoples R China Zhengzhou Univ Sch Water Conservancy & Transportat Zhengzhou 450001 Henan Peoples R China

Hinge joints are crucial for transverse force transfer in prestressed hollow slab bridges. Damages to hinge joints cause overall instability, load distribution changes, and reduced bearing capacity of the bridge. A new method using model updating and the orthogonal matching pursuit (OMP) algorithm is proposed to accurately assess the damage of hinge joints in such bridges using a single measurement point. The hinge joint damage index obtained by the OMP algorithm is assigned to the corresponding hinge joint in the FE model to complete the model update. Results show that this method can accurately identify hinge joint damage locations and degrees with a single measurement point. The damage identification of 12 hinge joints of an in-service hollow slab bridge is carried out, and the findings reveal that the damage occurred on the fourth, fifth, and seventh hinge joints.

关键词： Hinge joint damage Model updating orthogonal matching pursuit algorithm Hollow slab bridge Vertical displacement

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Thermal Light Longitudinal Correlated Imaging with Random orthogonal matching pursuit algorithm

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INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE 2018年第12期32卷

作者： Gao, Lu Xiao, Ke Song, Hanquan Qi, Xiaoman China Univ Geosci Sch Sci Beijing 100875 Peoples R China China Univ Geosci Sch Land Sci & Technol Beijing 100083 Peoples R China

A thermal light correlated longitudinal imaging experiment is proposed. The quasi-thermal light beam is split into two beams, a test beam and a reference beam, respectively. The light in the test beam is scattered by two amplitude objects with a specific longitudinal distance between them, while the light of the reference beam travels uninterrupted. At the end of the test and reference beams, two charge-coupled detectors (CCDs) are used to measure the intensity of the optical field. Through intensity correlation measurement the images of the two detected objects can be achieved simultaneously, only if the distance between the objects is less than the longitudinal coherent length. The theoretical analysis shows that the longitudinal coherent length is determined by both the transverse size of the incoherent thermal light source and the length of the optical path. The quality of the correlated images of the two objects is improved greatly by making use of the orthogonal matching pursuit (OMP) and the proposed variant random orthogonal matching pursuit (Random-OMP) algorithms. The experimental results show that the Random-OMP algorithm is more effective than the OMP algorithm for increasing both the visibility and continuity of the images. The experimental scenario can mimic an optical tomography imaging system, and the two objects with longitudinal distance can be taken as the two transverse layers of a three-dimensional object. The proposed Random-OMP algorithm is effective for improving the quality of the tomography image and has potential value in optical tomography imaging technology using incoherent light sources.

关键词： Ghost imaging orthogonal matching pursuit algorithm correlation measurement

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Optimization design and FPGA Implementation of orthogonal matching pursuit algorithm

Optimization design and FPGA Implementation of orthogonal ma...

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第五届国际自动化测试与仪器仪表学术会议

作者： Mo Yujun Bai Zhengyao Huang Zhen Dong Liang Zhou Yan School of Information Science and Engineering Yunnan University

In reconstruction algorithm of Compressed Sensing,it needs to gather more Information sample points for real-time signal streams whose sparsity is *** it is extremely difficult to implement the high-dimensional matrix multiplication on *** paper presented a novel hardware architecture for orthogonal matching pursuit(OMP)*** algorithm was improved to reduce the number of *** Cholesky Decomposition(ACD)which avoids square root calculations was used in the part of matrix decomposition to decrease computation *** parallel implementation and resource multiplexing were utilized to improve computing speed and resource *** design was described by using RTL HDL,implemented with Altera's PFGA Cyclone Ⅱ *** timing simulation was carried under the Quartus Ⅱ.Simulation results verify the correctness of the design.

关键词： FPGA Compressed Sensing orthogonal matching pursuit algorithm Alternative Cholesky Decomposition

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An orthogonal matching pursuit based algorithm for identification of a class of closed-loop systems 28

An orthogonal matching pursuit based algorithm for identific...

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28th Chinese Control and Decision Conference

作者： Han, Xue Liu, Yanjun Jiangnan Univ Minist Educ Key Lab Adv Proc Control Light Ind Wuxi 214122 Peoples R China Jiangnan Univ Sch Internet Things Engn Wuxi 214122 Peoples R China

ISBN: (纸本)9781467397148

This paper considers the identification problem of a class of closed-loop systems with large time-delays. Both the control plant and the feedback controller are required to be identified. The threshold orthogonal matching pursuit (TH-OMP) algorithm is applied to identify the closed-loop system indirectly. The identification contains two steps. The first is to identify the orders, time delays and the plant parameters using the TH-OMP algorithm. The second step is to identify the parameters of the feedback controller. The proposed method requires only a small number of sampling data. A simulation example is given to illustrate the effectiveness of the proposed algorithm.

关键词： Compressed sensing sparse parameter identification order identification orthogonal matching pursuit algorithm time-delay estimation

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