Results 41 to 50 of about 1,446,045 (274)
A Novel Strategy for Radar Imaging Based on Compressive Sensing [PDF]
, 2010 Radar data have already proven to be compressible with no significant losses for most of the applications in which it is used. In the framework of information theory, the compressibility of a signal implies that it can be decomposed onto a reduced set of
López-Dekker, Paco +8 more
core +1 more source
Energy-efficient sensing in wireless sensor networks using compressed sensing [PDF]
, 2014 Sensing of the application environment is the main purpose of a wireless sensor network. Most existing energy management strategies and compression techniques assume that the sensing operation consumes significantly less energy than radio transmission ...
Razzaque, Mohammad Abdur +5 more
core +1 more source
Frequency-difference sparse Bayesian learning for unambiguous direction-of-arrival estimation [PDF]
JASA Express LettersThe frequency-difference (FD) method uses the FD Hadamard product, comprising auto-products to model below-band acoustic fields and unintended cross-products, for efficient direction-of-arrival (DOA) estimation under spatial aliasing.
Ze Yuan +3 more
doaj +1 more source
Leida xuebao, 2016 Nowadays, high-speed sampling and transmission is a foremost challenge of radar system. In order to solve this problem, a compressive sensing approach is proposed for radar target signals in this study.
Zhong Jinrong, Wen Gongjian
doaj +1 more source
Robust Bayesian compressed sensing with outliers
Signal Processing, 2017 Abstract We consider the problem of robust compressed sensing where the objective is to recover a high-dimensional sparse signal from compressed measurements partially corrupted by outliers. A new sparse Bayesian learning method is developed for this purpose.
Qian Wan 0003 +4 more
openaire +3 more sources
Wavelet-Based Compressed Sensing for SAR Tomography of Forested Areas [PDF]
, 2012 Synthetic aperture radar (SAR) tomography is a 3-D imaging modality that is commonly tackled by spectral estimation techniques. Thus, the backscattered power along the cross-range direction can be readily obtained by computing the Fourier spectrum of a ...
Nannini, Matteo +2 more
core +1 more source
Bayesian Compressed Sensing with Heterogeneous Side Information [PDF]
2016 Data Compression Conference (DCC), 2016 The classical compressed sensing (CS) paradigm can be modified so as to leverage a signal correlated to the signal of interest, called side information, which is assumed to be provided a priori at the decoder in order to aid reconstruction. In this work, we propose a novel CS reconstruction method based on belief propagation principles, which manages ...
Evangelos Zimos +3 more
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Convolutional compressed sensing using deterministic sequences [PDF]
, 2012 This is the author's accepted manuscript (with working title "Semi-universal convolutional compressed sensing using (nearly) perfect sequences"). The final published article is available from the link below. Copyright @ 2012 IEEE.
Cong Ling +4 more
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Bayesian compressive sensing for primary user detection
IET Signal Processing, 2016 In compressive sensing (CS)‐based spectrum sensing literature, most studies consider accurate reconstruction of the primary user signal rather than detection of the signal. Furthermore, possible absence of the signal is not taken into account while evaluating the spectrum sensing performance.
Başaran, Mehmet +3 more
openaire +2 more sources
Fast monostatic scattering analysis based on Bayesian compressive sensing [PDF]
, 2017 In conjugation with the method of moments, the Bayesian compressive sensing algorithm is utilized to fast analyze the monostatic electromagnetic scattering problem.
Wei E. I. Sha +5 more
core +1 more source