0000000000789725

AUTHOR

Jaan Praks

0000-0001-7466-3569

showing 3 related works from this author

Feasibility study for a nanosatellite-based instrument for in-situ measurements of radio noise

2015

The radio environment on the earth is heavily affected by manmade sources such as radio transmissions, radars, and the like. The effect is particularly strong at MF frequencies and below, since the signals can propagate large distances via ionospheric bounce. Terrestrial magnetometer measurements have long been used to predict the Kp index, which is related to radio transmission at these ranges. Space weather measurements and models can also predict propagation of MF signals on the ground.

In situRadio transmissionMeteorologyMagnetometerlawPhysics::Space PhysicsEnvironmental scienceSpace weatherIonospherePhysics::GeophysicsRadio waveRemote sensinglaw.invention2015 1st URSI Atlantic Radio Science Conference (URSI AT-RASC)
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Aalto-1, multi-payload CubeSat: Design, integration and launch

2021

The design, integration, testing, and launch of the first Finnish satellite Aalto-1 is briefly presented in this paper. Aalto-1, a three-unit CubeSat, launched into Sun-synchronous polar orbit at an altitude of approximately 500 km, is operational since June 2017. It carries three experimental payloads: Aalto Spectral Imager (AaSI), Radiation Monitor (RADMON), and Electrostatic Plasma Brake (EPB). AaSI is a hyperspectral imager in visible and near-infrared (NIR) wavelength bands, RADMON is an energetic particle detector and EPB is a de-orbiting technology demonstration payload. The platform was designed to accommodate multiple payloads while ensuring sufficient data, power, radio, mechanica…

Computer sciencePolar orbitFOS: Physical sciencesAerospace Engineering02 engineering and technologyDesign strategy01 natural sciences7. Clean energyPhysics - Space Physicsmittauslaitteet0203 mechanical engineering0103 physical sciencesBrakeAalto-1CubeSatGround segmentAerospace engineeringInstrumentation and Methods for Astrophysics (astro-ph.IM)010303 astronomy & astrophysicsavaruustekniikkaAalto spectral imagerRadiation monitortutkimussatelliitit020301 aerospace & aeronauticsRadiationSpacecraftbusiness.industryPayloadCubeSatElectrostatic plasma brakesäteilySpace Physics (physics.space-ph)satelliititHyperspectralSatelliteAstrophysics - Instrumentation and Methods for Astrophysicsbusinesskosminen säteily
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PHYSICS-based retrieval of scattering albedo and vegetation optical depth using multi-sensor data integration

2017

Vegetation optical depth and scattering albedo are crucial parameters within the widely used τ-ω model for passive microwave remote sensing of vegetation and soil. A multi-sensor data integration approach using ICESat lidar vegetation heights and SMAP radar as well as radiometer data enables a direct retrieval of the two parameters on a physics-derived basis. The crucial step within the retrieval methodology is the calculus of the vegetation scattering coefficient KS, where one exact and three approximated solutions are provided. It is shown that, when using the assumption of a randomly oriented volume, the backscatter measurements of the radar provide a sufficient first order estimate and …

010504 meteorology & atmospheric sciencesScattering albedo0208 environmental biotechnologyradiometry02 engineering and technologyretrieval methodologycomputer.software_genre01 natural scienceslaw.inventionlawremote sensing by radarRadaractive-passive microwavesPhysics::Atmospheric and Oceanic PhysicsIndexespassive microwave remote sensingRemote sensingremote sensing by laser beamGeographyLidaroptical radarcrucial parametersmedicine.symptomvegetation scattering coefficientData integrationBackscattervegetation mappingta1171τ-ω modelsoilPhysics::GeophysicsICESat lidar vegetation heightsvegetationmedicineVegetation optical depthbackscatter0105 earth and related environmental sciencesRemote sensingsensor fusionRadiometerScatteringnovel multisensor approachSMAPAlbedoMulti-sensor020801 environmental engineeringradiometer dataVegetation (pathology)multisensor data integration approachcomputerICESatalbedo
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