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For wideband spectrum sensing, compressive sensing has been proposed as a solution to speed up the high dimensional signals sensing and reduce the computational complexity. Compressive sensing consists of acquiring the essential information from a sparse signal and recovering it at the receiver based on an efficient sampling matrix and a reconstruction technique. In order to deal with the uncertainty,...
For retrieving information in a wireless sensor network (WSN) from any node, each node must know the status of the entire network, leading to a high cost of energy in communication and information storage. In this paper, we evaluated a recovery method to request information from any node of a WSN with the use of compress sensing to compact the data to be stored and transmitted, and the use of a gossip...
Most of the existing cameras consist of lens and sensors. However, with the rapid development of semiconductor technology, the large size, high-budget and post-fabrication assembly of the lens have seriously restricted the development of the camera. This paper aims to solve the problems existing in the current lens-based camera and designs a new non-lens camera prototype exploiting the computational...
Confidentiality, entity authentication and nonrepudiation are security mechanisms, used to protect data against unauthorized access or manipulation. Hereby, the security and the reliability directly depend on the key. To secure a communication using Compressive Sensing (CS), the measurement matrix can be used as a key if it fulfill some requirements. However, the negotiation and the exchange of this...
Due to the poor spectrum utilization in time and space, the spectrum in cognitive radio is not only sparse but clusters in blocks in many situations. Based on the fact, a novel Bayesian compressed sensing algorithm for wideband spectrum sensing is proposed. In our proposed framework, firstly, the original signal should be sampled with sub-Nyquist sampling rate. Secondly, the clustering of the spectrum...
In this paper, arrivals of Head waves and multipaths are combined to estimate the sediments' compressional speeds and thicknesses. Compressive sensing (CS) is utilized to estimate the times of arrival and is compared with matched filter (MF). It shows that CS obtains much higher resolution and lower sidelobes than MF. With the times of arrival estimated, a two-step procedure is employed to estimate...
In ultra-wideband non-destructive testing of large multilayered polymers, data collection and reduction can be achieved by applying compressed sensing techniques. In this work, using effective modelling of possible defects, such as air gaps between layers, we construct defect dictionaries and use them as support data for a signal similarity-based classifier, which will automatically extract the main...
This paper presents a new technique for acoustic transducers position offset compensation, based on compressive sensing reconstruction in the warped domain. In underwater acoustics, the transducers relative position is important for applications involving direction of arrival estimation, localization or source detection. When the transmitter-receiver transducers configuration is inappropriate, the...
Most of the already existing spectrum detection algorithms are based on each channel sensing, which lowers the spectrum detection efficiency and makes detecting the spectrum holes promptly very difficult. Traditional MIMO systems are based on 2D MIMO spatial channel models, but in fact the real channel is 3D characterized. This paper proposes a novel scheduling scheme for cylindrical antenna based...
Smartphones with various embedded sensors and wirelessly connected external sensors will enable new applications across a wide variety of domains. Continuous or long-term sensing, processing, and communication of sensor data using smartphones will consume a significant amount of energy of the resource-constrained smartphones. Compression techniques, including predictive coding (PC) and compressed...
Wide-bandwidth lossless current sensors are critical in numerous applications, from current monitoring in DC-DC converters to non-invasive load monitoring. CMOS Hall sensor is a low-cost solution for current sensing and can be easily integrated as part of mixed-signal system-on-chips (SoCs). State-of-the-art CMOS Hall sensors offer only limited acquisition bandwidths of a few hundred kHz. This paper...
In [1], [2], two schemes have been proposed to recover the support of a K-sparse N-dimensional signal from noisy linear measurements. Both schemes use left-regular sparse-graph code based sensing matrices and a simple peeling-based decoding algorithm. Both the schemes require O(K logN) measurements and the first scheme require O(N logN) computations whereas the second scheme requires O(K logN) computations...
Radar-detection metrics are assessed in outcomes of sparse-signal processing (SSP) with test statistics based on the subgradient and the dual feasibility in the SSP optimization via an approach separating false alarms (FAs) from targets. In radar, SSP is aimed for estimating a sparse solution whose FAs are fixed and whose detection of targets is optimal as in traditional detection. Existing detection...
In pulsed Time-of-Flight (ToF) systems the pulse width establishes a tradeoff between depth resolution and range. Ideally, one would wish to emit a pulse that is as short as allowed by the hardware, while keeping the depth range arbitrarily large, being able to sense more than one return per pixel. This suggests the use of compressive sensing (CS) as sensing paradigm, in order to exploit the sparsity...
Synthetic Aperture Radar (SAR) interferometry has been the subject of an intensive development in the last years thanks to crucial applications in the area of risk monitoring. The emergence of very high resolution X-Band sensors has increased the interest in application to urban area. Advances of SAR interferometry has been provided by the extension toward SAR tomography. By transforming classical...
This paper proposes a new sparse spectrum sensing framework for cognitive radars, by combining the ideas of coprime sampling and atomic norm line spectrum estimation. Cognitive radars need to scan a large frequency band to detect presence of other radio users and find available spectral holes for opportunistic transmission. This necessitates the use of expensive A/D converters operating at very high...
The implementation of computational sensing strategies often faces calibration problems typically solved by means of multiple, accurately chosen training signals, an approach that can be resource-consuming and cumbersome. Conversely, blind calibration does not require any training, but corresponds to a bilinear inverse problem whose algorithmic solution is an open issue. We here address blind calibration...
This paper introduces a new scenario, named combined based on minimum distance orthogonal matching pursuit (CMD-OMP) which utilizes the strength of two available recovery methods at different ranges of minimum distance. Particularly, OMP with a global optimization and non-negative constrained least square algorithm (a MATLAB function implemented as OMP with a modification step) will be studied comparatively...
In this paper, the clipping noise estimation problem based on compressed sensing (CS) is investigated when the subcarriers used for creating measurement vector are on the edge of the frequency band. Although selection of such subcarriers would not degrade data rate and is suitable for systems requiring high rates, it still weakens the performance of CS recovery algorithms especially in the presence...
FANET is co-operative, reconfigurable, autonomous network of UAVs. The emerging technology of FANET has many applications in civilian and military field like search and rescue mission, surveillance, reconnaissance, monitoring etc. which create temporary mobile ad-hoc platform for communication and data collection. For such applications, main requirements are maintaining and sustaining connectivity...
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