Search results for " sensing"

showing 10 items of 1517 documents

SHARP: Environment and Person Independent Activity Recognition with Commodity IEEE 802.11 Access Points

2022

In this article we present SHARP, an original approach for obtaining human activity recognition (HAR) through the use of commercial IEEE 802.11 (Wi-Fi) devices. SHARP grants the possibility to discern the activities of different persons, across different time-spans and environments. To achieve this, we devise a new technique to clean and process the channel frequency response (CFR) phase of the Wi-Fi channel, obtaining an estimate of the Doppler shift at a radio monitor device. The Doppler shift reveals the presence of moving scatterers in the environment, while not being affected by (environment-specific) static objects. SHARP is trained on data collected as a person performs seven differe…

Signal Processing (eess.SP)Networking and Internet Architecture (cs.NI)FOS: Computer and information scienceshuman activity recognitionMobile computingComputer Science - Machine LearningCFRMonitoringSensorsComputer Networks and CommunicationsIEEE 802.11acneural networksWi-Fi sensingMachine Learning (cs.LG)Computer Science - Networking and Internet ArchitectureCSIActivity recognitionFOS: Electrical engineering electronic engineering information engineeringPerformance evaluationFeature extractionWireless fidelityElectrical and Electronic EngineeringElectrical Engineering and Systems Science - Signal Processingcontactless indoor monitoringSoftware
researchProduct

A probabilistic compressive sensing framework with applications to ultrasound signal processing

2019

Abstract The field of Compressive Sensing (CS) has provided algorithms to reconstruct signals from a much lower number of measurements than specified by the Nyquist-Shannon theorem. There are two fundamental concepts underpinning the field of CS. The first is the use of random transformations to project high-dimensional measurements onto a much lower-dimensional domain. The second is the use of sparse regression to reconstruct the original signal. This assumes that a sparse representation exists for this signal in some known domain, manifested by a dictionary. The original formulation for CS specifies the use of an l 1 penalised regression method, the Lasso. Whilst this has worked well in l…

Signal processing0209 industrial biotechnologyBayesian methodsComputer scienceTKAerospace Engineering02 engineering and technologycomputer.software_genre01 natural sciencesRelevance vector machineNDTSettore ING-IND/14 - Progettazione Meccanica E Costruzione Di Macchine020901 industrial engineering & automationLasso (statistics)0103 physical sciencesUltrasoundUncertainty quantification010301 acousticsSparse representationCivil and Structural EngineeringSignal processingSignal reconstructionMechanical EngineeringProbabilistic logicSparse approximationCompressive sensingComputer Science ApplicationsCompressed sensingControl and Systems EngineeringRelevance Vector MachineData miningcomputer
researchProduct

A fluorescence retrieval method for the flex sentinel-3 tandem mission

2014

A new fluorescence retrieval method is proposed to support ESA's 8th Earth Explorer Fluorescence EXplorer (FLEX) candidate mission. Most hyperspectral fluorescence retrieval algorithms available in the literature are very sensitive to true reflectance modelization and/or they assume the atmospheric status as known. The proposed algorithm delivers the retrieval of full fluorescence spectrum at canopy level by using only Top Of Atmosphere (TOA) radiances as input. The proposed method starts with (1) the atmospheric correction of TOA radiances, characterizing the state of the atmosphere without assuming any a-priori classification on aerosols models, (2) performing a first estimation of fluore…

Signal processingComputer sciencesynergy productFluorescence retrievalAtmospheric correctionHyperspectral imagingAtmospheric modelFluorescenceFLEXAtmosphereAtmospheric correctionSentinel-3Adaptive opticsAbsorption (electromagnetic radiation)Remote sensing2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)
researchProduct

Optical encryption with compressive ghost imaging

2011

Ghost imaging (GI) is a novel technique where the optical information of an object is encoded in the correlation of the intensity fluctuations of a light source. Computational GI (CGI) is a variant of the standard procedure that uses a single bucket detector. Recently, we proposed to use CGI to encrypt and transmit the object information to a remote party [1]. The optical encryption scheme shows compressibility and robustness to eavesdropping attacks. The reconstruction algorithm provides a relative low quality images and requires high acquisitions times. A procedure to overcome such limitations is to combine CGI with compressive sampling (CS), an advanced signal processing theory that expl…

Signal processingLight intensityCompressed sensingbusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingReconstruction algorithmIterative reconstructionGhost imagingEncryptionbusinessAlgorithm2011 Conference on Lasers and Electro-Optics Europe and 12th European Quantum Electronics Conference (CLEO EUROPE/EQEC)
researchProduct

Introduction to Digital Signal Processing

2018

Signal processing deals with the representation, transformation, and manipulation of signals and the information they contain. Typical examples include extracting the pure signals from a mixture observation (a field commonly known as deconvolution) or particular signal (frequency) components from noisy observations (generally known as filtering). This chapter outlines the basics of signal processing and then introduces the more advanced concepts of time‐frequency and time‐scale representations, as well as emerging fields of compressed sensing and multidimensional signal processing. When moving to multidimensional signal processing, a modern approach is taken from the point of view of statis…

Signal processingMultidimensional signal processingCompressed sensingComputer sciencebusiness.industryDeconvolutionLaplacian matrixbusinessRepresentation (mathematics)AlgorithmSignalDigital signal processing
researchProduct

Proba-V cloud detection Round Robin: Validation results and recommendations

2017

This paper discusses results from 12 months of a Round Robin exercise aimed at the inter-comparison of different cloud detection algorithms for Proba-V. Clouds detection is a critical issue for satellite optical remote sensing, since potential errors in cloud masking directly translates into significant uncertainty in the retrieved downstream geophysical products. Cloud detection is particularly challenging for Proba-V due to the presence of a limited number of spectral bands and the lack of thermal infrared bands. The main objective of the project was the inter-comparison of several cloud detection algorithms for Proba-V over a wide range of surface types and environmental conditions. Prob…

Signal processingPixelArtificial neural networkbusiness.industryCloud computingSpectral bandsLinear discriminant analysiscomputer.software_genreThresholdingGeographySatelliteData miningbusinesscomputerRemote sensing2017 9th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp)
researchProduct

An Effective Satellite Remote Sensing Tool Combining Hardware and Software Solutions

2019

In this paper we propose a new effective remote sensing tool combining hardware and software solutions as an extension of our previous work. In greater detail the tool consists of a low cost receiver subsystem for public weather satellites and a signal and image processing module for several tasks such as signal and image enhancement, image reconstruction and cloud detection. Our solution allows to manage data from satellites effectively with low cost components and portable software solutions. We aim at sampling and processing of the modulated signal entirely in software enabled by Software Defined Radios (SDR) and CPU computational speed overcoming hardware limitation such as high receive…

Signal processingSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni010504 meteorology & atmospheric sciencesComputer scienceNoise (signal processing)business.industryBandwidth (signal processing)0211 other engineering and technologiesImage processing02 engineering and technologySoftware-defined radioCloud detectionRemote sensing01 natural sciencesSoftwareDemodulationWeather satelliteSatellite communicationSoftware architecturebusinessComputer hardware021101 geological & geomatics engineering0105 earth and related environmental sciences
researchProduct

Energy balance in single exposure multispectral sensors

2013

International audience; Recent simulations of multispectral sensors are based on a simple Gaussian model, which includes filters transmittance and substrate absorption. In this paper we want to make the distinction between these two layers. We discuss the balance of energy by channel in multispectral solid state sensors and propose an updated simple Gaussian model to simulate multispectral sensors. Results are based on simulation of typical sensor configurations.

SiliconMaterials science[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processingoptical sensorsChannel (digital image)Equations[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPhotodetectorGaussian processes02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural sciences010309 opticssymbols.namesakeMathematical model[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical sciences0202 electrical engineering electronic engineering information engineeringTransmittanceComputer Science::Networking and Internet ArchitectureSpectral and color filter arraysoptical filtersOptical filterGaussian processPhysics::Atmospheric and Oceanic Physics[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingRemote sensingtransmittance filterSubstratesSensorsGaussian modelmultispectral solid state sensorCamerasenergy balancespectral analysisConvolutionexposure multispectral sensorComputer Science::Computer Vision and Pattern Recognitionsubstrate absorptionlight absorptionlight sensorsymbolstransmittance filters020201 artificial intelligence & image processingGaussian network model[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingEnergy (signal processing)
researchProduct

Calibration of the SARI portable rainfall simulator for field and laboratory experiments

2019

The Simulator of Artificial RaInfall (SARI) rainfall simulator (RS) is a newly designed, constructed and calibrated, portable, two-nozzle RS with low water consumption, accurate measurement, easy m...

Simulated rainfallField (physics)Rainfall simulatorCalibrationEnvironmental scienceWater consumptionWater Science and TechnologyRemote sensingHydrological Sciences Journal
researchProduct

Design and operation of a small and portable rainfall simulator for rugged terrain

1997

A rainfall simulator designed to perform experiments in rugged terrain is presented. The portability of the apparatus allows the researcher to work in remote areas and on steep slopes. Rainfall intensity and distribution within the plot (0.24 m2) and drop-size were measured under different water pressure. For the best simulated rainfall distribution (1.55 kg cm2 of water pressure and 55 mm h−1 of rain intensity) the drop velocity and the kinetic energy were measured.

Simulated rainfallMeteorologyRain intensityRainfall simulatorDrop (liquid)General EngineeringEnvironmental scienceTerrainWater pressureRemote sensingSoil Technology
researchProduct