Gridless DOA Estimation with Extended Array Aperture in Automotive Radar Applications by Pengyu Jiang, Silin Gao, Jie Zhao, Zhe Zhang, Bingchen Zhang

“…However, traditional compressed sensing algorithms generally assume that targets are located on a finite set of grid points and perform sparse reconstruction based on predefined grids. …”
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Improving Rare Events Detection in WSN through Cluster-Based Power Control Mechanism by Zakia Jellali, Leïla Najjar Atallah, Sofiane Cherif

“…Rare events detection is one of the main applications in Wireless Sensor Networks (WSN) and is currently a central concern of a vast literature. Compressed Sensing (CS) theory has been proved to be quite adapted to this objective. …”
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Music Segmentation Algorithm Based on Self-Adaptive Update of Confidence Measure by Jianhua Li

“…According to the theory of compressed sensing, the music fragments are denoised, and thus the denoised signals are subjected to short-term correlation analysis. …”
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Hybrid genetic algorithm based optimization of pilotpattern by Hanbing ZHENG, Xiang YU, Weiwei WANG

“…In OFDM system,sparse channel estimation based on compressed sensing(CS)can make full use of the inherent sparse degree of the wireless channel,which can reduce the pilot overhead and improve the spectrum efficiency.Therefore,a new method based on hybrid genetic algorithm was investigated for the pilot design of CS channel estimation,which was based on the minimization of the matrix cross correlation in the CS theory.In this method,genetic algorithm was used to obtain the initial sub-optimal pilot sequence,and then combined with the pilot position and pilot power,each entry of pilot pattern could be sequentially updated and optimized to make the minimum correlation of measurement matrix.Simulation results show that the proposed method can ensure a better mean square error and bit error rate compared to the pseudo-random pilot design and the equal distance pilot design.…”
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Robust Linear Neural Network for Constrained Quadratic Optimization by Zixin Liu, Yuanan Liu, Lianglin Xiong

“…Finally, a numerical simulation example and an application example in compressed sensing problem are also given to illustrate the validity of the criteria established in this paper.…”
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Accelerated dynamic light sheet microscopy: unifying time-varying patterned illumination and low-rank and sparsity constrained reconstruction by Marco Tobia Vitali, Alessia Candeo, Andrea Farina, Paolo Pozzi, Alessia Brix, Andrea Bassi, Teresa M Correia

“…To address this limitation, we recently developed spatially modulated Selective Volume Illumination Microscopy, which utilizes a compressed sensing approach to reconstruct the entire imaging volume from measurements where multiple planes are illuminated simultaneously using spatially modulated light. …”
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Receiver design of sparse Bayesian learning based MIMO-OFDM power line communication system by Xinrong LYU, Youming LI, Yongqing WU, Xiaobo TANG

“…The rich impulsive noise in the power line channel poses a huge challenge to the design of MIMO-OFDM transceiver.To solve this problem, a design scheme that can jointly estimate the channel and impulsive noise was proposed, which exploited the parametric sparsity of the classical multipath model and the sparsity of the time domain impulsive noise.In this scheme, the unknown channel model parameters and the impulsive noise were jointly regarded as a sparse vector.By observing the spatial correlation of MIMO system, a compressed sensing model based on multiple measurement vectors was constructed.The multiple response sparse Bayesian learning theory was introduced to jointly estimate the MIMO channel parameters and impulsive noise.The simulation results show that, compared with the traditional receiver scheme that considers MIMO channel estimation and impulsive noise suppression separately, the receiver proposed has a significant improvement in channel estimation performance and bit error rate performance.…”
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NLOS location enhancement algorithm based on depth-first multipath parameter estimation by Xiaofeng LU, Ye DONG, Yuejie LI

“…In order to improve the positioning accuracy of millimeter wave system with non-line-of-sight (NLOS) paths, a depth-first multipath parameter estimation algorithm was proposed based on distributed compressed sensing.According to the evaluated multipath parameters, NLOS path could be identified, so that the localization performance was enhanced.Firstly, depth-first algorithm was applied to reduce the unnecessary path searching, and the more accurate multipath parameters were obtained.Secondly, under the reverse positioning distance residual method, NLOS path recognition could be carried out.Then, the scatterers in the NLOS path were matched, and the position of which were regarded as virtual anchor nodes.Combining the information of base stations and virtual anchor nodes, positioning enhancement was realized.Finally, localization performance of the proposed algorithm was simulated, compared with the distance weighted least square (LS) and maximum discrimination transformation (MDT) algorithms, the performance of the proposed algorithm is improved by 17% and 8% respectively.…”
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Comparing Two Approaches for Point-Like Scatterer Detection by Angela Dell’Aversano, Giovanni Leone, Raffaele Solimene

“…Accordingly, in this paper we compare the time reversal-MUSIC and the compressed sensing. The study develops through numerical examples and focuses on the role of noise in data and mutual coupling between the scatterers.…”
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Sparse Optimization of Vibration Signal by ADMM by Song Wanqing

“…In this paper, the alternating direction method of multipliers (ADMM) algorithm is applied to the compressed sensing theory to realize the sparse optimization of vibration signal. …”
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Global convergence in a modified RMIL-type conjugate gradient algorithm for nonlinear systems of equations and signal recovery by Yan Xia, Songhua Wang

“… (4) Numerical experiments indicated that the proposed algorithm surpasses existing similar algorithms in both efficiency and stability, particularly when applied to large scale nonlinear systems of equations and signal recovery problems in compressed sensing.…”
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SVM Intrusion Detection Model Based on Compressed Sampling by Shanxiong Chen, Maoling Peng, Hailing Xiong, Xianping Yu

“…We use compressed sampling method in the compressed sensing theory to implement feature compression for network data flow so that we can gain refined sparse representation. …”
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MRI Reconstruction with Separate Magnitude and Phase Priors Based on Dual-Tree Complex Wavelet Transform by Wei He, Linman Zhao

“…The methods of compressed sensing magnetic resonance imaging (CS-MRI) can be divided into two categories roughly based on the number of target variables. …”
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An Adaptive Prediction-Correction Method for Solving Large-Scale Nonlinear Systems of Monotone Equations with Applications by Gaohang Yu, Shanzhou Niu, Jianhua Ma, Yisheng Song

“…Some practical applications of the proposed method are demonstrated and tested on sparse signal reconstruction, compressed sensing, and image deconvolution problems.…”
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A Sparsity Preestimated Adaptive Matching Pursuit Algorithm by Xinhe Zhang, Yufeng Liu, Xin Wang

“…In the matching pursuit algorithm of compressed sensing, the traditional reconstruction algorithm needs to know the signal sparsity. …”
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Efficient Cross-Layer Optimization Algorithm for Data Transmission in Wireless Sensor Networks by Chengtie Li, Jinkuan Wang, Mingwei Li

“…Firstly, congestion control and link allocation are separately provided at transport layer and network layer, by supply and demand based on compressed sensing (CS). Secondly, we propose the cross-layer scheme to minimize the power cost of the whole network by a linear optimization problem. …”
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Research Progress in Methods to Estimate High-resolution Direction of Arrival by Wei ZHAO, Xuan LI, Chengpeng HAO

“…Then, it analyzes the reasons for the limited resolution of traditional beamforming-based methods and discusses higher-resolution methods such as adaptive beamforming direction spectrum, subspace methods, and compressed sensing. Furthermore, for the needs of practical applications, the paper summarizes the progress of broadband target DOA estimation methods, sparse array-based DOA estimation methods, and two-dimensional DOA estimation methods. …”
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Indoor terminal localization technology using a single access point based on distributed MIMO networks by Ze LI, Jian ZOU, Zeng HUANG, Zengshan TIAN

“…Regarding the terminal localization in distributed MIMO networks, an indoor terminal localization system using a single access point (AP) based on distributed MIMO networks was proposed.Firstly, the AP’s antennas were arranged at different locations in the room, and the compressed sensing algorithm was used to estimate the angle of departure (AoD) and time of flight (ToF) of the receiving path on each antenna of the terminal device.Secondly, AoDs and ToFs of multiple paths were combined to establish a nonlinear localization model, and an improved Levenberg-Marquardt algorithm was used to solve the problem.Then, theoretical analysis has been examined for the factors that influence the localization error, and the criteria for the antenna layout was provided.Finally, electromagnetic simulation software was used to build simulation environment and conducted the simulation for system verification.Moreover, software-defined radio platforms were used to conduct practical tests.Both simulation and experimental results indicate that the performance of the proposed localization system is superior to existing single-AP localization systems based on natural multipath.…”
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Channel Estimation in DCT-Based OFDM by Yulin Wang, Gengxin Zhang, Zhidong Xie, Jing Hu

“…We also study a compressed sensing (CS) based channel estimation, which takes the sparse property of wireless channel into account. …”
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A Novel Decentralized Scheme for Cooperative Compressed Spectrum Sensing in Distributed Networks by Huang Jijun, Zha Song

“…Compressed sensing (CS) recently turns out to be an effective approach to alleviate the sampling bottleneck in wideband spectrum sensing. …”
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