H∞ LIDAR odometry for spacecraft relative navigation - Kechagias-Stamatis, Odysseas; Aouf, Nabil (Institution of Engineering and Technology (IET), 2016)
Current light detection and ranging (LIDAR) based odometry solutions that are used for spacecraft relative navigation suffer from quite a few deficiencies. These include an off-line training requirement and relying on the iterative closest point (ICP) that does not guarantee a globally optimum solution. To encounter this, the authors suggest a robust architecture that overcomes the problems of current proposals by combining the concepts of 3D local feature matching with an adaptive variant of the H∞ recursive filtering process. Trials on real laser scans of an EnviSat model demonstrate that the proposed architecture affords at least one order of magnitude better accuracy compared to ICP.
Keywords: motion estimation; space vehicles; feature extraction; recursive filters; distance measurement; iterative methods; optical radar; navigation; image registration; aerospace computing; image matching