Terrain Relative Navigation Using Crater Identification in Surface Topography Data

This paper explores three different crater identification algorithms for use in spacecraft navigation relative to a celestial body that use topography data obtained by active sensors, such as a flash LIDAR. Topography data was selected over visible images since the active sensors that produce topography data are lighting independent, and NASA desires the ability to perform precision landing at any time, and at locations such as the Lunar South Pole where the solar incidence angle is always low. Two of the algorithms explored are modified versions of existing algorithms developed for use with visible images, and one is a new method developed for topography data. Evaluation of the algorithms is made on the basis of the rate of false crater identifications and the resulting position and orientation error using test data covering eight regions within the data sets available from the Mars Orbiting Laser Altimeter and the Lunar Orbiting Laser Altimeter. All of the algorithms performed adequately, with the image morphology method performing slightly better.

[1]  Brian D. Bue,et al.  Machine Detection of Martian Impact Craters From Digital Topography Data , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[2]  David E. Smith,et al.  Mars Orbiter Laser Altimeter: Experiment summary after the first year of global mapping of Mars , 2001 .

[3]  Michael C. Burl,et al.  Automated detection of craters and other geological features , 2001 .

[4]  Luc Van Gool,et al.  Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..

[5]  Joe P. Golden,et al.  Terrain Contour Matching (TERCOM): A Cruise Missile Guidance Aid , 1980, Optics & Photonics.

[6]  Larry H. Matthies,et al.  The Mars Exploration Rovers Descent Image Motion Estimation System , 2004, IEEE Intell. Syst..

[7]  J. Muller,et al.  Automated crater detection, a new tool for Mars cartography and chronology , 2005 .

[8]  Christian J. Grund,et al.  Intensified imaging photon-counting technology for enhanced flash lidar performance , 2010, Defense + Commercial Sensing.

[9]  M. Uijt_de_Haag,et al.  Flight Test Evaluation of Various Terrain Referenced Navigation Techniques for Aircraft Approach Guidance , 2006, 2006 IEEE/ION Position, Location, And Navigation Symposium.

[10]  Luc Van Gool,et al.  SURF: Speeded Up Robust Features , 2006, ECCV.

[11]  David E. Smith,et al.  Initial observations from the Lunar Orbiter Laser Altimeter (LOLA) , 2010 .

[12]  Ding Meng,et al.  Autonomous Craters Detection from Planetary Image , 2008, 2008 3rd International Conference on Innovative Computing Information and Control.

[13]  Maarten Uijt de Haag,et al.  Application of laser range scanner based terrain referenced navigation systems for aircraft guidance , 2006, Third IEEE International Workshop on Electronic Design, Test and Applications (DELTA'06).

[14]  Francis Chad Hanak Lost in low lunar orbit crater pattern detection and identification , 2009 .

[15]  A.E. Johnson,et al.  Overview of Terrain Relative Navigation Approaches for Precise Lunar Landing , 2008, 2008 IEEE Aerospace Conference.

[16]  Ricardo Vilalta,et al.  Automatic detection of craters in planetary images: an embedded framework using feature selection and boosting , 2010, CIKM.

[17]  Pedro Pina,et al.  Impact Crater Recognition on Mars Based on a Probability Volume Created by Template Matching , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[18]  Soumya Ghosh,et al.  Machine Learning for Automatic Mapping of Planetary Surfaces , 2007, AAAI.