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Autonomous aerial refueling (AAR) is an important capability for an unmanned aerial vehicle (UAV) to increase its flying range and endurance without increasing its size. This paper presents a novel tracking method that utilizes both 2D intensity and 3D point-cloud data acquired with a 3D Flash LIDAR sensor to establish relative position and orientation between the receiver vehicle and drogue during an aerial refueling process. Unlike classic, vision-based sensors, a 3D Flash LIDAR sensor can provide 3D point-cloud data in real time without motion blur, in the day or night, and is capable of imaging through fog and clouds. The proposed method segments out the drogue through 2D analysis and estimates the center of the drogue from 3D point-cloud data for flight trajectory determination. A level-set front propagation routine is first employed to identify the target of interest and establish its silhouette information. Sufficient domain knowledge, such as the size of the drogue and the expected operable distance, is integrated into our approach to quickly eliminate unlikely target candidates. A statistical analysis along with a random sample consensus (RANSAC) is performed on the target to reduce noise and estimate the center of the drogue after all 3D points on the drogue are identified. The estimated center and drogue silhouette serve as the seed points to efficiently locate the target in the next frame.

This paper reviews the progress of Advanced Scientific Concepts, Inc (ASC). flash ladar 3-D imaging systems and presents their newest single-pulse 128 x 128 flash ladar 3-D images. The heart of the system, a multifunction ROIC based upon both analog and digital processing, is described. Of particular interest is the obscuration penetration function, which is illustrated with a series of images. An image tube-based low-laser-signal 3-D FPA is also presented. A small-size handheld working version of the 3-D camera is illustrated which uses an InGaAs lensed PIN detector array indium bump bonded to the ROIC.