Sliding-Mode Observer-based Navigation Algorithms and Artificial Potential Fields for Space Proximity Operations

This paper proposes Sliding-Mode Observer (SMO) and Artificial Potential Field (APF) as Navigation and Guidance algorithms for space applications. Both robust linear first-order and Super-Twisting SMOs are designed for performing sensor filtering measurements. Optical cameras and accelerometers are considered as sensors. A comparison with an Extended Kalman Filter (EFK) is proposed, in order to show the effectiveness of SMOs as alternative navigation algorithms. Harmonic 3D functions for the APF algorithm are proposed to manage issues related to the presence of local minima. Moreover, the repulsive field is changed for including moving targets and obstacles. Finally, the effectiveness of these algorithms is shown through numerical simulations, achieving results suitable for autonomous Rendezvous and Proximity Operations.