Abstract This article addresses the localization of a Gliding Vehicle (GV) deployed from an airplane. The GV's goal is to hit a target precisely. Assume that the GV cannot employ the Global Navigation Satellite System (GNSS) for locating itself. For instance, a GNSS signal can be jammed as the GV is close to a target, since the target can jam the GNSS signal of the incoming GV. On the other hand, the airplane is far from the target, and the airplane can employ GNSS for locating itself. As the GV is launched from the airplane, the GV locates itself employing its on‐board Inertial Measurement Units (IMU) and Time‐Of‐Arrival (TOA) between the GV and the airplane. IMU‐only localization results in the integration of localization error as time goes on; thus, TOA is used to fix the integrated localization error. This research employs the Extended Kalman Filter (EKF) for solving the hybrid IMU‐TOA localization problem. As far as we know, this study is novel in addressing hybrid IMU‐TOA localization of a vehicle (GV in our paper) deployed by another vehicle (airplane in our paper), which can employ GNSS. We show that the proposed hybrid IMU‐TOA localization can improve the localization accuracy, compared to the case where the GV employs IMU only. The effectiveness of the proposed localization strategy is demonstrated utilizing MATLAB simulations.
Jonghoek Kim (Sat,) studied this question.