- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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P-OMP-IR ALGORITHM FOR HYBRID PRECODING IN MILLIMETER WAVE MIMO SYSTEMS
摘要： This paper presents a P-OMP-IR algorithm for the hybrid precoding problem in millimeter wave (mm-Wave) multiple-input multiple-output (MIMO) systems. In the proposed approach, the digital precoding matrix is updated via the orthogonal matching pursuit (OMP) method, and the analog precoding matrix is re?ned column by column using the dominant singular value and corresponding singular vectors of a residual matrix successively. During the re?ning phase of the analog precoding matrix, an extended power method is designed to calculate the dominant singular value and the corresponding left and right singular vectors, which is able to reduce the computational complexity signi?cantly. Simulation results show that the proposed algorithm can not only reduce the residual of the hybrid precoder e?ectively, but also improve the spectral e?ciency consistently.
关键词： millimeter wave,MIMO systems,orthogonal matching pursuit,P-OMP-IR algorithm,spectral efficiency,hybrid precoding
更新于2025-09-23 15:21:01
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Compressive Sensing Holographic Microwave Random Array Imaging of Dielectric Inclusion
摘要： Holographic microwave imaging is an innovative method to image biological objects based on their dielectric properties, which has the advantages of high spatial resolution. However, the image reconstruction method is always a critical issue in holographic microwave imaging. This research aims to investigate the feasibility and effectiveness of applying compressive sensing (CS) technique to the holographic microwave imaging for small dielectric object detection. This paper presents a compressive sensing holographic microwave random array imaging (CS-HMRAI) method for imaging of dielectric objects. A numerical system consists of various dielectric models and imaging processing model are developed to evaluate the proposed approach. The split Bregman (SB) and orthogonal matching pursuit (OMP) algorithms are applied to HMRAI for evaluation of small inclusions embedded in dielectric objects. Various experiments are conducted to identify lesions using the proposed CS-HMRAI method and results are compared with HMRAI and HMRAI via OMP methods. Both simulation and experimental results demonstrate that CS-HMRAI via SB can produce high-quality images and detect arbitrarily shaped small inclusions with random sizes and locations by using significantly fewer sensors and scanning times than the HMRAI and CS-HMRAI via OMP approaches. The proposed approach has the potential for further investigation for breast tumor detection in a fast and cost-effective manner.
关键词： Microwave imaging,orthogonal matching pursuit,compressive sensing,holographic microwave imaging,split Bregman
更新于2025-09-11 14:15:04
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[IEEE 2018 25th IEEE International Conference on Image Processing (ICIP) - Athens, Greece (2018.10.7-2018.10.10)] 2018 25th IEEE International Conference on Image Processing (ICIP) - Matching Pursuit Based on Kernel Non-Second Order Minimization
摘要： The orthogonal matching pursuit (OMP) is an important sparse approximation algorithm to recover sparse signals from compressed measurements. However, most MP algorithms are based on the mean square error (MSE) to minimize the recovery error, which is suboptimal when there are outliers. In this paper, we present a new robust OMP algorithm based on kernel non-second order statistics (KNS-OMP), which not only takes advantages of the outlier resistance ability of correntropy but also further extends the second order statistics based correntropy to a non-second order similarity measurement to improve its robustness. The resulted framework is more accurate than the second order ones in reducing the effect of outliers. Experimental results on synthetic and real data show that the proposed method achieves better performances compared with existing methods.
关键词： kernel non-second order measurement,correntropy,sparse recovery,Orthogonal matching pursuit
更新于2025-09-11 14:15:04
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[IEEE 2018 Conference on Precision Electromagnetic Measurements (CPEM 2018) - Paris, France (2018.7.8-2018.7.13)] 2018 Conference on Precision Electromagnetic Measurements (CPEM 2018) - A New Measurement Method for Supraharmonics in 2–150 kHz
摘要： The 32 equal-width segments supraharmonics measurement method, recommended in the newly revised standard IEC 61000-4-30, has some disadvantages, such as the large frequency resolution, and the large effect of spectral leakage. To overcome this, a new measurement method for supraharmonics in 2-150 kHz based on compressive sensing is proposed. Simulation results and measured data analysis indicate that the proposed approach can overcome DFT algorithm’s limitation, and the frequency resolution can be improved by an order-of-magnitude without extending the signal’s observation time. The amplitude of supraharmonics can also be calculated accurately.
关键词： Compressive sensing,orthogonal matching pursuit,measurement,power electronics,supraharmonics
更新于2025-09-10 09:29:36
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3-D IMAGING OF HIGH-SPEED MOVING SPACE TARGET VIA JOINT PARAMETRIC SPARSE REPRESENTATION
摘要： The high-speed moving of space targets introduces distortion and migration to range pro?le, which will have a negative e?ect on three-dimensional (3-D) imaging of targets. In this paper, based on joint parametric sparse representation, a 3-D imaging method for high-speed moving space target is proposed. First, the impact of high speed on range pro?le of target is analyzed. Then, based on an L-shaped three-antenna interferometric system, a dynamic joint parametric sparse representation model of echoes from three antennas is established. The dictionary matrix is re?ned by iterative estimation of velocity. Moreover, an improved orthogonal matching pursuit (OMP) algorithm is proposed to recover interferometric phase information. Finally, with the phase information, interferometric processing is conducted to obtain the 3-D image of target scatterers. The simulation results verify the e?ectiveness of the proposed method.
关键词： 3-D imaging,orthogonal matching pursuit (OMP) algorithm,interferometric processing,joint parametric sparse representation,high-speed moving space target
更新于2025-09-09 09:28:46
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A sparse representation method for image-based surface defect detection
摘要： In this paper, an efficient sparse representation-based method is presented for detecting surface defects. The proposed method uses the sparse degree of coefficient in the redundant dictionary for checking whether the test image is defective or not, and the binary representation of the defective images is obtained, according to the global coefficient feature. Owing to the requirements for the efficiency and detecting quality, the block proximal gradient operator is introduced to speed up the online dictionary learning. Considering the correlation among the testing samples, prior knowledge is applied in the orthogonal-matching-pursuit sparse representation algorithm to improve the speed of sparse coding. Experimental results demonstrate that the proposed detection method can effectively detect and extract the defects of the surface images, and has broad applicability.
关键词： orthogonal-matching-pursuit,surface defect detection,block proximal gradient operator,sparse representation
更新于2025-09-04 15:30:14
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Fusion of United Sparse Principal Component Analysis Dictionary Based on Linear Unmixing Image Technique
摘要： Based on the linear unmixing images of different surface objects, online dictionary learning algorithm was utilized to compute the sparse dictionaries for multispectral linear unmixing images and panchromatic images. Principal component analysis (PCA) was then utilized to generate united sparse PCA dictionaries through the extraction of the first principal components of panchromatic images and unmixing image dictionaries. The number of dictionaries is determined to be 480 after taking into consideration of the limitation in computing power and root-mean-square error of restructured images. Based on these dictionaries, orthogonal matching pursuit method was utilized to calculate the sparse coefficients of multispectral and panchromatic images, separately, while nonnegative matrix factorization fusion algorithm was utilized to calculate multispectral and panchromatic sparse coefficients to obtain sparse coefficient of the fusional image on all bands, with the resulted matrix having a size of 480 × 255 025. These united sparse PCA dictionaries and fusion sparse coefficients were then used to reconstruct the fusional image. Through the analysis of five quantitative indices of fusion assessment, the proposed fusion algorithm has retained the multispectral information of images and enhanced the detailed information in image texture.
关键词： nonnegative matrix factorization (NMF) fusion,principal component analysis (PCA) dictionary,Linear unmixing,orthogonal matching pursuit (OMP) algorithm,online dictionary learning (ODL) algorithm
更新于2025-09-04 15:30:14