Kechagias-Stamatis, OdysseasAouf, Nabil2019-03-042019-03-042016-01-04Odysseas Kechagias-Stamatis and Nabil Aouf. H∞ LIDAR odometry for spacecraft relative navigation. IET Radar Sonar and Navigation, Volume 13, Issue 5, 2019, Article number 7711751-8784https://doi.org/10.1049/iet-rsn.2018.5354http://dspace.lib.cranfield.ac.uk/handle/1826/13962Current 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.enAttribution-NonCommercial 4.0 Internationalhttp://creativecommons.org/licenses/by-nc/4.0/motion estimationspace vehiclesfeature extractionrecursive filtersdistance measurementiterative methodsoptical radarnavigationimage registrationaerospace computingimage matchingArticle