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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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Performance Variability Modeling of Analog Circuits Using Improved orthogonal matching pursuit 19

Performance Variability Modeling of Analog Circuits Using Im...

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19th International SoC Design Conference (ISOCC) - SoC Technology Towards a New Era of Innovation

作者： Park, Hyunjun Choi, Woo-Seok Seoul Natl Univ Dept Elect & Comp Engn Interuniv Semicond Res Ctr Seoul South Korea

ISBN: (纸本)9781665459716

Process variations have a significant impact on performance and yield in the nanoscale design of integrated circuits (ICs). Monte Carlo simulation is useful in predicting these variations due to its simple implementation. However, the simulation cost of this method increases exponentially as the number of random parameters increases. In this paper, we solve these problems by using an Improved OMP algorithm based on sparse regression. The proposed algorithm solved heuristically L-0 regularization problem and effectively model performance based on a limited number of simulation samples. Numerical results for circuit designed in a 28nm process demonstrate that IOMP achieves up to 1.625x speedup compared to the traditional OMP method.

关键词： orthogonal matching pursuit algorithm Integrated circuit Process variation Sparse Regression

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Template-Based 2D High-Precision Model Reconstruction of Car Body

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IEEE ACCESS 2023年 11卷 35608-35619页

作者： Wang, Bo Yang, Zhiying Giannini, Franca Monti, Marina Li, Baojun Wuhan Univ Sci & Technol Sch Automobile & Traff Engn Wuhan 430065 Peoples R China CNR Inst Appl Math & Informat Technol I-16149 Genoa Italy Dalian Univ Technol Sch Automot Engn Dalian 116024 Peoples R China

Car body design includes the construction of car sketches, 2D models and 3D models. The establishment of high-quality car body models usually relies on CAD software, which requires the proficient operating skills, and the efficiency is relatively low compared with automatic modeling. The time cost of communication between the designer and the model engineer will also affect the modeling efficiency. How to quickly and automatically generate high quality parametric models from car sketches or images efficiently has become a development direction for the automotive design. In this paper, we propose a template-based reconstruction method of 2D high-precision car body model. On the basis of the established 2D model database, a coarse model is achieved by the improved orthogonal matching pursuit algorithm with few key points which are obtained by deep neural network;further, according to the proposed auto-fitting optimization algorithm of cubic Bezier curve, the modeling process of "from coarse to fine" is realized combining edge information. The proposed template-based 2D high-precision model reconstruction algorithm of the car body can greatly reduce the modeling time under the given modeling accuracy.

关键词： Automobiles Solid modeling matching pursuit algorithms Image edge detection Image reconstruction Parametric statistics Fitting Automotive engineering Bezier curve fitting key points extraction orthogonal matching pursuit algorithm car body reconstruction

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Structural Damage Identification Based on Extended Kalman Filter and Response Reconstruction

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IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF CIVIL ENGINEERING 2023年第5期47卷 2673-2687页

作者： Liu, Mandong Peng, Zhenrui Dong, Qi Lanzhou Jiaotong Univ Sch Mech Engn Lanzhou 730070 Peoples R China

Aiming at the problems of low signal precision and uncertain sparsity in traditional structural damage identification methods, a structural damage identification method based on an extended Kalman filter and response reconstruction technology is proposed. Firstly, the extended Kalman filter is used for signal filtering analysis, and the standard deviation of the filtered signal is calculated to preliminarily analyze the damage location of the structure. Secondly, the Kalman filter is used for data fusion of the filtered signal, and the orthogonal matching pursuit algorithm of compressed sensing reconstruction is introduced to set the signal sparsity range and reconstruct the response. When the reconstructed signal meets the accuracy requirements of the Euclidean norm relative error, the standard deviations of the reconstructed signal are used to identify the damage location, and the damage degree of the structure is determined by the relationship between the signal standard deviation before and after the damage. The identification effect is verified by the damage location and degree of ASCE benchmark structure story and truss structure rod elements. The results show that the proposed method has certain reliability.

关键词： Extended Kalman filter Data fusion orthogonal matching pursuit algorithm Response reconstruction

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Some results on OMP algorithm for MMV problem

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MATHEMATICAL METHODS IN THE APPLIED SCIENCES 2022年第9期45卷 5402-5411页

作者： Zhang, Xiwen Xie, Liejun Wang, Jinping Ningbo Univ Sch Math & Stat Ningbo 315211 Peoples R China

In this paper, the robustness of the orthogonal matching pursuit (OMP) algorithm for multiple measurement vector (MMV) problem under the restricted isometry property (RIP) is presented. Moreover, it is shown that the OMP algorithm can exactly recover K-row sparse matrices in K iterations under the RIP condition we have presented. Furthermore, the condition is sharp.

关键词： compressed sensing multiple measurement vector orthogonal matching pursuit algorithm restricted isometry property

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An improved local oscillator modulation of modulated sampling scheme for multiple mono-pulse radar signals reconstruction

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EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING 2022年第1期2022卷 1-22页

作者： Qiu, Zhaoyang Sun, Minhong Zhu, Jun Teng, Xuyang Song, Huina Hangzhou Dianzi Univ Sch Commun Engn Hangzhou Peoples R China Guoke Dianlei Beijing Elect Equipment Technol Co Chengdu Peoples R China

The modulated sampling scheme can intercept noncooperative signals distributed in a wide frequency band by using a single receiving channel, which is an efficient architecture in many radar and communication applications. The modulated sampling scheme employs a non-uniform sample pulse train to fold the intercepted signal prior to quantization/digitization by using a local oscillator (LO) that contains a certain modulation type. Since the mono-pulse radar signals are widely used in many radar systems, the modulated sampling scheme will receive the multiple mono-pulse radar signals simultaneously in dense signal environment, and the folded outputs of the modulated sampling scheme may meet frequency aliasing. Thus, it is necessary to investigate the reconstruction of the multiple mono-pulse signals intercepted by the modulated sampling scheme in the frequency aliasing situation. In this paper, based on the orthogonal matching pursuit algorithm, the LO modulation type of the modulated sampling scheme is analyzed to achieve a better reconstruction performance of the multiple mono-pulse signals. The drawback of the typical LO using sinusoidal frequency modulation to reconstruct multiple mono-pulse signals is investigated firstly. Then, an improved LO using periodic linear frequency modulation is proposed, and its effectiveness to reconstruct multiple mono-pulse signals is analyzed. Furthermore, the parameter setting criterion of the improved LO modulation is given, and the comparison using other modulation types is discussed. Finally, several simulations are conducted to prove our analysis and the improved LO modulation can reconstruct multiple mono-pulse signals under the frequency aliasing condition.

关键词： Modulated sampling scheme Multiple mono-pulse signals Local oscillator modulation Signal reconstruction orthogonal matching pursuit algorithm

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Low pilot overhead channel estimation for CP-OFDM-based massive MIMO OTFS system

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IET COMMUNICATIONS 2022年第10期16卷 1071-1082页

作者： Li, Tong Han, Chuang Yao, Rugui Fan, Ye Zuo, Xiaoya Northwestern Polytech Univ Sch Elect & Informat Xian Peoples R China

In high-speed mobile scenarios, due to the high-speed relative motion between transmitter and receiver, the high Doppler frequency shift interferes with the inter-subcarrier orthogonality in orthogonal frequency-division multiplexing (OFDM) systems. Therefore its performance is significantly degraded. Recently, orthogonal time-frequency space (OTFS) is considered as an effective alternative scheme to OFDM for time-varying channels. As with OFDM-massive multiple input multiple output (MIMO) systems, downlink channel estimation is necessary for OTFS-massive MIMO systems to improve the spectral efficiency in frequency-division duplex (FDD) mode without channel reciprocity. Here, first the cyclic prefix -OFDM-based massive MIMO OTFS system channel with antenna directivity pattern is analyzed, and transform the burst sparsity in the angle domain into block sparsity by using non-uniform Fourier transform (NUFT). Furthermore, to solve the problem that the pilot overhead grows linearly with the number of antennas, we propose a three-dimensional (3D) dynamic support detect (DSD) algorithm. Compared with the traditional OMP algorithm, and the 3D-structured orthogonal matching pursuit algorithm, simulation results demonstrate the proposed DSD algorithm has higher channel estimation accuracy, and lower pilot overhead.

关键词： frequency-division duplex mode orthogonal frequency-division multiplexing systems channel reciprocity OTFS-massive MIMO systems MIMO communication time-frequency analysis high-speed relative motion radio transceivers downlink channel estimation channel estimation massive MIMO OTFS system channel inter-subcarrier orthogonality multiple input multiple output systems OFDM-massive CP-OFDM-based massive MIMO OTFS system time-varying channels orthogonal matching pursuit algorithm Fourier transforms orthogonal time-frequency space iterative methods higher channel estimation accuracy OFDM modulation high Doppler frequency shift antenna radiation patterns mobile scenarios low pilot overhead channel estimation antenna arrays

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Fractional Delay and Doppler Estimation for OTFS Based ISAC Systems

Fractional Delay and Doppler Estimation for OTFS Based ISAC ...

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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Zacharia, Olivia Devi, Vani M. Indian Inst Space Sci & Technol Dept Avion Thiruvananthapuram Kerala India

ISBN: (纸本)9781665491228

In this paper, we consider an orthogonal time frequency space (OTFS) modulation based single input single output (SISO) radar for integrated sensing and communication (ISAC) where the transmitter sends OTFS frames and the radar receiver co-located with the transmitter leverages the transmit frame along with the reflected signal for the estimation of the target range and velocity. We present a novel radar channel model that is capable of capturing both integer as well as fractional delays and Doppler shifts accounted for by the targets in the channel. A two-step modified orthogonal matching pursuit with fractional refinement (OMPFR) algorithm is also proposed to estimate the delays and Doppler shifts that can be non-integer multiples of the system delay and Doppler resolutions respectively. We show that our algorithm has much lower complexity than the traditional orthogonal matching pursuit (OMP) algorithm if used in estimating the fractional delays and Dopplers, as the latter requires a colossal dictionary matrix. Target profiles and the root mean square error (RMSE) plots for range and velocity estimates validate the effectiveness of the proposed OMPFR algorithm.

关键词： ISAC Monostatic radar OTFS orthogonal matching pursuit algorithm Sparse signal processing Target detection

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A novel DOA estimation method for uncorrelated and coherent signals via compressed sensing in sparse arrays

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ELECTRONICS LETTERS 2021年第25期57卷 995-997页

作者： Han, Peng Xu, Haiyun Cui, Weijia Zhang, Yankui Ba, Bin Natl Digital Switching Syst Engn & Technol Res Ct Zhengzhou Henan Peoples R China

When there is the coexistence of uncorrelated and coherent signals in sparse arrays, the conventional algorithms using coarray are fail. In order to solve this problem, the letter proposes a novel method based on compressed sensing. Firstly, the authors vectorize the covariance matrix and establish a sparse representation model through constructing a two-dimensional redundant dictionary. Then, the authors use an improved orthogonal matching pursuit algorithm for off-grid sources to recover the sparse vector. Through analysing location of non-zero elements in sparse vector, the direction-of-arrivals of both uncorrelated and coherent signals can be obtained. The proposed method has no strict limitation by the structure of the existing sparse arrays. Moreover, it makes full use of vectorized data and can estimate more number of signals than that of sensors. Numerical experiments prove the effectiveness and favourable performance of the proposed method.

关键词： signal representation covariance matrix approximation theory compressed sensing sparse arrays DOA estimation sparse representation vectors direction-of-arrivals non-zero elements direction-of-arrival estimation covariance matrices array signal processing orthogonal matching pursuit algorithm sparse vector

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Radar recognition of multiple micro-drones based on their micro-Doppler signatures via dictionary learning

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IET RADAR SONAR AND NAVIGATION 2020年第9期14卷 1310-1318页

作者： Zhang, Wenyu Li, Gang Baker, Chris Tsinghua Univ Dept Elect Engn Beijing Peoples R China Univ Birmingham Dept Elect Elect & Syst Engn Birmingham W Midlands England

Most existing work on radar classification of micro-drones assumes that the received signal is wholly reflected from a single micro-drone. However, when there are multiple micro-drones in the observed scene, the superimposition of their micro-Doppler signatures increases the classification difficulty. In particular, it is even more challenging to determine if a specific type of micro-drones exists. In this study, a method for recognition of multiple micro-drones based on their micro-Doppler signatures via dictionary learning is introduced. First, the dictionary is learnt for each type of micro-drone by using the K-SVD algorithm on cadence-velocity diagrams (CVD) of training samples. The CVD is obtained by computing the Fourier transform of the time series of a complex time-frequency spectrogram. Subsequently, the sparse representation of the CVD of multiple micro-drones is obtained by the orthogonal matching pursuit algorithm with the learnt dictionary. Finally, a threshold detector is applied to the sparse solution in order to extract the components of multiple micro-drones. Experimental results using measured data, which are collected from hovering drones by a continuous-wave radar in an indoor environment, show that this dictionary-learning-based method achieves a recognition performance of 93% when half of the measured data are used for training.

关键词： radar signal processing singular value decomposition Doppler radar signal representation signal classification Fourier transforms radar target recognition learning (artificial intelligence) radar computing time series approximation theory CW radar multiple microdrones microDoppler signatures single microdrone radar recognition dictionary learning K-SVD algorithm cadence-velocity diagrams Fourier transform time series complex time-frequency spectrogram orthogonal matching pursuit algorithm radar classification

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