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Detection of high frequency plasma waves and interplanetary dust by Solar Orbiter RPW-TDS instrument

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    0517675 - ÚFA 2020 US eng A - Abstract
    Souček, Jan - Uhlíř, Luděk - Lán, Radek - Píša, David - Kolmašová, Ivana - Santolík, Ondřej - Krupař, Vratislav - Krupařová, Oksana - Maksimovic, M.
    Detection of high frequency plasma waves and interplanetary dust by Solar Orbiter RPW-TDS instrument.
    AGU Fall Meeting. Washington: American Geophysical Union, 2019. SH21D-3298.
    [AGU Fall Meeting 2019. 09.12.2019-13.12.2019, San Francisco]
    Institutional support: RVO:68378289
    Keywords : plasma waves * interplanetary dust * electromagnetic waveform measurements
    OECD category: Fluids and plasma physics (including surface physics)
    https://agu.confex.com/agu/fm19/meetingapp.cgi/Paper/537327

    The Radio and Plasma Wave instrument (RPW) for Solar Orbiter includes a Time Domain Sampler sub-unit (TDS) designed to capture electromagnetic waveform measurements of high frequency plasma waves and antenna voltage spikes associated with dust impacts. TDS will digitize three components of the electric field and one magnetic component at 524 kHz sampling rate and scan the obtained signal for plasma waves and dust impact signatures. The main science target of TDS are Langmuir waves observed in the solar wind in association with Type II and Type III solar bursts, interplanetary shocks, magnetic holes, and other phenomena. TDS implements a dedicated algorithm to identify those narrowband modulated waves and extract their properties. Using this on-board logic, TDS will attempt to choose the best waveform snapshots, containing interesting events, for downlink to the ground. At the same time, TDS will collect statistics of measured signals and build histograms of parameters of observed waves and dust impacts. We present the design of the instrument, its scientific modes and data products. We focus on the on-board data processing algorithms used in event identification and the assessment of their performance on test datasets based on STEREO data.

    Permanent Link: http://hdl.handle.net/11104/0302983

     
     
Number of the records: 1  

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