Autonomous Navigation of Unmanned Aircraft Using Space Target LOS Measurements and QLEKF

Abstract

An autonomous navigation method based on the fusion of INS (inertial navigation system) measurements with the line-of-sight (LOS) observations of space targets is presented for unmanned aircrafts. INS/GNSS (global navigation satellite system) integration is the conventional approach to achieving the long-term and high-precision navigation of unmanned aircrafts. However, the performance of INS/GNSS integrated navigation may be degraded gradually in a GNSS-denied environment. INS/CNS (celestial navigation system) integrated navigation has been developed as a supplement to the GNSS. A limitation of traditional INS/CNS integrated navigation is that the CNS is not efficient in suppressing the position error of the INS. To solve the abovementioned problems, we studied a novel integrated navigation method, where the position, velocity and attitude errors of the INS were corrected using a star camera mounted on the aircraft in order to observe the space targets whose absolute positions were available. Additionally, a QLEKF (Q-learning extended Kalman filter) is designed for the performance enhancement of the integrated navigation system. The effectiveness of the presented autonomous navigation method based on the star camera and the IMU (inertial measurement unit) is demonstrated via CRLB (Cramer–Rao lower bounds) analysis and numerical simulations.