Abstract:The student-built Agricultural Camera (AgCam) now onboard the International Space Station observes the Earth surface through two linescan cameras with Charge-Coupled Device (CCD) arrays sensitive to visible and near-infrared wavelengths, respectively. The electro-optical components of the AgCam were characterized using precision calibration equipment; a method for modeling and applying these measurements was derived. Correction coefficients to minimize effects of optical vignetting, CCD non-uniform quantum efficiency, and CCD dark current are separately determined using a least squares fit approach. Application of correction coefficients yields significant variability reduction in flat-field images; comparable results are obtained when applied to ground test images.

As a near orbit space platform, the International Space Station (ISS) has been increasingly used for Earth observing applications. This paper presents a quaternion-based forward geolocation algorithm for Earth observing sensors onboard the ISS. The input parameters include the orbital state and attitude information of the ISS and the look vector of the sensor. The proposed algorithm agrees with the commercial navigation product, Satellite Tool Kit ® , within 0.5 m in ideal situations. The inherent uncertainties in ISS attitude and state determinations, and the International Space Station Agriculture Camera (ISSAC) tilting angle were estimated to introduce an error less than 800 m. However, the actual geolocation error evaluated using the images obtained by the ISSAC is roughly 4 km, much greater than the inherent uncertainty and mainly due to (a) delay caused by the Windows ® operating system in acquiring images, and (b) the misalignment of the ISSAC sensor coordinate system with the ISS body-fi xed coordinate system. A preliminary cal/val process using the Google Earth ™ as reference was performed to quantify these two errors, the correction of which improved the geolocation accuracy to 500 m, well within the inherent uncertainty.

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