NASA's Langley Research Center (LaRC) is sponsoring the development of a revolutionary new concept for remote sensing from space, which has been termed a sensorcraft. Sensorcraft designates a space flight remote measurement, and the spacecraft bus, which provides the operational resources needed by the instrument in orbit. The small size and integrated nature of the design of both the instrument and spacecraft bus can provide a 10 X reduction in estimated mission costs for atmospheric remote sensing. The gas and aerosol monitoring sensorcraft, GAMS, measure vertical distributions of ozone, water vapor, aerosols, temperature, and pressure in the atmosphere from the mid-troposphere through the stratosphere. A key feature of GAMS is the use of extensive onboard data processing to reduce the sensorcraft size and weight, and thereby reduce total mission cost. The GAMS real-time digital signal processing (DSP) data processing algorithm reduces the instrument's raw data volume by a factor of 30. Combined with post event processing that achieves a similar reduction, the total GAMS data volume is reduced by a factor of approximately 1000 from that of the current generation of space-based remote sensors. The numerical techniques used in the real-time algorithm, including the fundamental assumptions made about the measurement error in the data and its relationship to the processing will be discussed.


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    Titel :

    Real-time digital signal processing enables a reduced-cost atmospheric remote sensorcraft


    Beteiligte:
    Grant, M.S. (Autor:in) / Sandford, S.P. (Autor:in)


    Erscheinungsdatum :

    01.01.1998


    Format / Umfang :

    660908 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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