Wideband Spectrum Sensing: A Bayesian Compressive Sensing Approach [PDF]
Sensors, 2018 Sensing the wideband spectrum is an important process for next-generation wireless communication systems. Spectrum sensing primarily aims at detecting unused spectrum holes over wide frequency bands so that secondary users can use them to meet their ...
Youness Arjoune, Naima Kaabouch
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Resolution Enhancement for Millimeter-Wave Radar ROI Image with Bayesian Compressive Sensing [PDF]
Sensors, 2022 For millimeter-wave (MMW) imaging security systems, the image resolution promisingly determines the performance of suspicious target detection and recognition. Conventional synthetic aperture radar (SAR) imaging algorithms only provide limited resolution
Pengfei Xie +4 more
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Sparse Reconstruction of Sound Field Using Bayesian Compressive Sensing and Equivalent Source Method [PDF]
Sensors, 2023 To solve the problem of sound field reconstruction with fewer measurement points, a sound field reconstruction method based on Bayesian compressive sensing is proposed.
Yue Xiao +4 more
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Bayesian Compressive Sensing of Sparse Signals with Unknown Clustering Patterns [PDF]
Entropy, 2019 We consider the sparse recovery problem of signals with an unknown clustering pattern in the context of multiple measurement vectors (MMVs) using the compressive sensing (CS) technique. For many MMVs in practice, the solution matrix exhibits some sort of
Mohammad Shekaramiz +2 more
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Two-Tier PSO Based Data Routing Employing Bayesian Compressive Sensing in Underwater Sensor Networks [PDF]
Sensors, 2020 Underwater acoustic sensor networks play an important role in assisting humans to explore information under the sea. In this work, we consider the combination of sensor selection and data routing in three dimensional underwater wireless sensor networks ...
Xuechen Chen, Wenjun Xiong, Sheng Chu
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Multi-Frequency GPR Microwave Imaging of Sparse Targets through a Multi-Task Bayesian Compressive Sensing Approach [PDF]
Journal of Imaging, 2021 An innovative inverse scattering (IS) method is proposed for the quantitative imaging of pixel-sparse scatterers buried within a lossy half-space. On the one hand, such an approach leverages on the wide-band nature of ground penetrating radar (GPR) data ...
Marco Salucci, Nicola Anselmi
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Variational Bayesian Compressive Sensing with Equivalent Source Modeling for Sound Field Reconstruction [PDF]
SensorsWhile conventional Bayesian compressive sensing exploits signal sparsity for accurate sound field reconstruction from under-sampled measurements, its practicality is limited by high computational complexity and slow convergence.
Yue Xiao +3 more
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Bayesian Compressive Sensing Based Optimized Node Selection Scheme in Underwater Sensor Networks [PDF]
Sensors, 2018 Information acquisition in underwater sensor networks is usually limited by energy and bandwidth. Fortunately, the received signal can be represented sparsely on some basis. Therefore, a compressed sensing method can be used to collect the information by
Ruisong Wang +5 more
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A Sound Source Identification Algorithm Based on Bayesian Compressive Sensing and Equivalent Source Method [PDF]
Sensors, 2020 Near-field acoustic holography (NAH) based on equivalent source method (ESM) is an effective method for identifying sound sources. Conventional ESM focuses on relatively low frequencies and cannot provide a satisfactory solution at high frequencies.
Ming Zan +3 more
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Data-adaptive pattern-coupled Bayesian compressive sensing for sparse sound field reconstruction [PDF]
Scientific ReportsPattern-coupled Bayesian compressive sensing shows great potential in sound field reconstruction by leveraging structural sparsity, but its fixed coupling patterns for sparsity hyperparameters limit adaptability to non-uniform correlation distributions ...
Yue Xiao +4 more
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