Initial results of a study on the use of flash LIDAR for relative pose and trajectory estimation are presented. Analysis is conducted for distant approach phases where flash LIDAR measurements are processed with no information about the target body shape and attitude, and for close approach phases where the relative pose is estimated simultaneously with the relative trajectory. In both cases, very good relative navigation accuracy can be obtained with errors based on current flash LIDAR models. The distant navigation analysis considered the necessary frequency of flash LIDAR data needed for accurate solutions, the effect of ignoring the target shape, and the growth of the achieved errors in the case of sensor malfunction. The close approach results are focused on the implementation of a combination of the Optimal Linear Attitude and Translation Estimator (OLTAE) algorithm for processing feature based tracking into relative attitude and translation measurements, combined with an extended Kalman filter (EKF) for estimating the full 6-DOF relative dynamic state.
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