Spaceborne laser-altimeter-pointing bias calibration from range residual analysis

For many science applications of laser altimetry, the precise location of the point on the Earth's surface from which the laser energy reflects is required. The geolocation accuracy of this illuminated laser bounce point is primarily dependent on the accuracy of the laser-pointing knowledge. Laser and spacecraft body systematic misalignments are significant contributors to the pointing knowledge error. We present a method fur accounting for these systematic misalignments through a Bayesian least-squares-estimation process using laser-altimeter range residuals. This range-residual calibration method uses commanded spacecraft attitude maneuvers and ocean range residuals for the recovery of the pointing and range biases. The performance of this method is evaluated through both consider-covariance and simulation studies applied to the upcoming Vegetation Canopy Lidar and the Ice and Cloud Elevation Satellite missions. The results of these analyses suggest are-second level pointing bias knowledge can be achieved. A calibration maneuver is developed for both the Vegetation Canopy Lidar and the Ice and Cloud Elevation Satellite mission. The laser altimeter-range measurement model algorithm is presented.