The Plasma Experiment for Planetary Exploration (PEPE) flown on Deep Space 1 combines an ion mass spectrometer and an electron spectrometer in a single, low-resource instrument. Among its novel features PEPE incorporates an electrostatically swept field-ofview and a linear electric field time-of-flight mass spectrometer. A significant amount of effort went into developing six novel technologies that helped reduce instrument mass to 5.5 kg and average power to 9.6 W. PEPE's performance was demonstrated successfully by extensive measurements made in the solar wind and during the DS1 encounter with Comet 19P/Borrelly in September 2001.

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A spatial-spectral classification technique for classification of materials within Hyperspectral images is described in this paper. The method considers the influence of neighboring pixels to apply local spatial context features to correctly label an unknown pixel. The spatial and spectral features are jointly applied to a Maximum Likelihood classifier that uses material class models defined by a Mixture of Gaussians to adaptively account for spectral variability and noise. Experimental results compare the application of spatial and spectral features with only spectral features on the classification of materials common to scenes viewed from the ground perspective.

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