Visual navigation for autonomous, precise and safe landing on celestial bodies using unscented Kalman filtering

This paper explores the state estimation problem for an autonomous precise landing approach on celestial bodies. As part of the project “Autonomous Terrain-based Optical Navigation” (ATON) of the German Aerospace Center (DLR) this paper describes the central state estimation algorithm. This algorithm combines high rate inertial navigation with low rate sensor fusion. The description includes the software architecture of the developed navigation system and the estimator, which is based on an Unscented Kalman Filter (UKF). The UKF equations are presented as well as the specific transition and observation models. Additionally, different image processing modules, providing the UKF with position updates, are described shortly. Finally, the evaluation of the implemented system based on performed flight tests imitating a landing on the Moon is presented. These tests show that the method is capable of providing a robust navigation solution during the landing approach.

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