Compressed Sensing in On-Grid MIMO Radar by Michael F. Minner

“…Recent advances of Compressive Sensing offer a means of efficiently accomplishing this task. …”
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Application of Compressive Sensing in Solving Monostatic Scattering Problems by Shui-Rong Chai, Li-Xin Guo, Long Li

“…In this paper, a new CS-FMM method that conjugates compressive sensing (CS) with the fast multipole method (FMM) is proposed and validated to efficiently solve monostatic scattering from an arbitrary conducting target. …”
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Compressed Sensing Based Fingerprint Identification for Wireless Transmitters by Caidan Zhao, Xiongpeng Wu, Lianfen Huang, Yan Yao, Yao-Chung Chang

“…Therefore, this paper proposes a new method to identify different wireless transmitters based on compressed sensing. A data acquisition system is designed to capture the wireless transmitter signals. …”
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Deterministic Sensing Matrices in Compressive Sensing: A Survey by Thu L. N. Nguyen, Yoan Shin

“…One of the most concerns in compressive sensing is the construction of the sensing matrices. …”
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Block Compressed Sensing of Images Using Adaptive Granular Reconstruction by Ran Li, Hongbing Liu, Yu Zeng, Yanling Li

“…In the framework of block Compressed Sensing (CS), the reconstruction algorithm based on the Smoothed Projected Landweber (SPL) iteration can achieve the better rate-distortion performance with a low computational complexity, especially for using the Principle Components Analysis (PCA) to perform the adaptive hard-thresholding shrinkage. …”
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Improved RIP Conditions for Compressed Sensing with Coherent Tight Frames by Yao Wang, Jianjun Wang

“…This paper establishes new sufficient conditions on the restricted isometry property (RIP) for compressed sensing with coherent tight frames. One of our main results shows that the RIP (adapted to D) condition δk+θk,k<1 guarantees the stable recovery of all signals that are nearly k-sparse in terms of a coherent tight frame D via the l1-analysis method, which improves the existing ones in the literature.…”
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Multi-Scale Channel Distillation Network for Image Compressive Sensing by Tianyu Zhang, Kuntao Ye, Yue Zhang, Rui Lu

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Compressed Sensing Based Apple Image Measurement Matrix Selection by Ying Xiao, Wanlin Gao, Ganghong Zhang, Han Zhang

“…The purpose of this paper is to design a measurement matrix of apple image based on compressed sensing to realize low cost sampling apple image. …”
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A Novel Coherence Reduction Method in Compressed Sensing for DOA Estimation by Jing Liu, ChongZhao Han, XiangHua Yao, Feng Lian

“…This method is then extended to a more practical condition when highly coherent columns and incoherent columns are considered, for example, the direction of arrival (DOA) estimation problem in phased array radar system using compressed sensing. Numerical simulations show that the proposed method succeeds in identifying multiple targets in a sparse radar scene, where the compressed sensing method based on the original sensing matrix fails. …”
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FPGA Implementation of Real-Time Compressive Sensing with Partial Fourier Dictionary by Yinghui Quan, Yachao Li, Xiaoxiao Gao, Mengdao Xing

“…This paper presents a novel real-time compressive sensing (CS) reconstruction which employs high density field-programmable gate array (FPGA) for hardware acceleration. …”
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Micro-Doppler Ambiguity Resolution Based on Short-Time Compressed Sensing by Jing-bo Zhuang, Zhen-miao Deng, Yi-shan Ye, Yi-xiong Zhang, Yan-yong Chen

“…In this paper, we propose a novel method based on compressed sensing (CS) to solve micro-Doppler ambiguity. …”
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Improved Compressed Sensing Reconfiguration Algorithm with Shockwave Dynamic Compensation Features by Mingchi Ju, Yingjie Dai, Tailin Han, Yingzhi Wang, Bo Xu, Xuan Liu

“…This paper proposes a regularized generalized orthogonal matching pursuit algorithm with dynamic compensation characteristics based on the application context of compressive sensing in shock wave signal testing. We add dynamic compensation denoising as a regularization condition to the reconstruction algorithm. …”
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Guaranteed Stability of Sparse Recovery in Distributed Compressive Sensing MIMO Radar by Yu Tao, Gong Zhang, Jindong Zhang

“…Low SNR condition has been a big challenge in the face of distributed compressive sensing MIMO radar (DCS-MIMO radar) and noise in measurements would decrease performance of radar system. …”
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Bayesian Compressive Sensing as Applied to Directions-of-Arrival Estimation in Planar Arrays by Matteo Carlin, Paolo Rocca, Giacomo Oliveri, Andrea Massa

“…The Bayesian compressive sensing (BCS) is applied to estimate the directions of arrival (DoAs) of narrow-band electromagnetic signals impinging on planar antenna arrangements. …”
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Compressed Sensing Photoacoustic Imaging Based on Fast Alternating Direction Algorithm by Xueyan Liu, Dong Peng, Wei Guo, Xibo Ma, Xin Yang, Jie Tian

“…At the cost of longer calculations, a compressive sensing reconstruction scheme can achieve artifact-free imaging with fewer measurements. …”
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A distributed estimation method over network based on compressed sensing by Lin Li, Donghui Li

“…The compressed sensing theory is introduced in the distributed estimation to further reduce the communication load as the unknown parameter of interest is sparse in many situations. …”
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The Sparsity Adaptive Reconstruction Algorithm Based on Simulated Annealing for Compressed Sensing by Yangyang Li, Jianping Zhang, Guiling Sun, Dongxue Lu

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Effects of ADC Nonlinearity on the Spurious Dynamic Range Performance of Compressed Sensing by Rongzong Kang, Pengwu Tian, Hongyi Yu

“…Analog-to-information converter (AIC) plays an important role in the compressed sensing system; it has the potential to significantly extend the capabilities of conventional analog-to-digital converter. …”
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Off-Grid DOA Estimation Based on Compressed Sensing on Multipath Environment by Bin Hu, Xueyong Shen, Min Jiang, Kaiheng Zhao

“…In this paper, an off-grid DOA estimation technique based on compressed sensing (CS) on multipath environment is proposed. …”
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Modified complex multitask Bayesian compressive sensing using Laplacian scale mixture prior by Qilei Zhang, Lei Yu, Feng He, Yifei Ji

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