We have developed a highly accurate support vector machine (SVM) based detector capable of identifying jarosite (K, Na, H/sub 3/O)Fe/sub 3/ (SO/sub 4/)/sub 2/(OH)/sub 6/) in the visible/NIR (350-2500 nm) spectra of both laboratory specimens and rocks in Mars analogue field environments. To keep the computational complexity of the detector to a minimum, we restricted our design to an SVM with a linear kernel and a small number of support vectors. We used our generative model to create linear mixtures of end-member library spectra to train the SVM. We validated the detector on museum quality laboratory samples (97% accuracy) and field rock samples measured in both the laboratory and the field (both 88% accuracy). In the interest of technology infusion, the detector has been integrated into the CLARAty autonomous mobile robotics software architecture.


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    Titel :

    Onboard detection of jarosite minerals with applications to Mars


    Beteiligte:
    Bornstein, B. (Autor:in) / Castano, R. (Autor:in) / Gilmore, M.S. (Autor:in) / Merrill, M. (Autor:in) / Greenwood, J.P. (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.01.2006


    Format / Umfang :

    459505 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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