Nonlinear Augmented Proportional Navigation for Midrange Rendezvous Guidance and Performance Assessment

Abstract

Guidance systems are important to autonomous rendezvous with uncooperative targets such as an active debris removal (ADR) mission. A novel guidance frame is established in rotating line-of-sight (LOS) coordinates, which resolves the coupling effect between pitch and yaw planes in a general 3D scenario. The guidance law is named augmented proportional navigation (APN) by applying nonlinear control along LOS and classical proportional navigation normal to LOS. As saving time is a critical factor in space rescue and on-orbit service, the finite time convergence APN (FTCAPN) is further proposed which proves to possess convergence and high robustness. This paper builds on previous efforts in polynomial chaos expansion (PCE) to develop an efficient analysis technique for guidance algorithms. A large scope of uncertainty sources are considered to make state evaluation trustworthy and provide precise prediction of trajectory bias. The simulation results show that the accuracy of the proposed method is compatible with Monte Carlo simulation which requires extensive computational effort.