A Kalman Approach to Lunar Surface Navigation using Radiometric and Inertial Measurements

Future lunar missions supporting the NASA Vision for Space Exploration will rely on a surface navigation system to determine astronaut position, guide exploration, and return safely to the lunar habitat. In this report, we investigate one potential architecture for surface navigation, using an extended Kalman filter to integrate radiometric and inertial measurements. We present a possible infrastructure to support this technique, and we examine an approach to simulating navigational accuracy based on several different system configurations. The results show that position error can be reduced to 1 m after 5 min of processing, given two satellites, one surface communication terminal, and knowledge of the starting position to within 100 m.