Tightly coupled integrated navigation system via factor graph for UAV indoor localization

Due to the widely use of the rotorcrafts in civil applications, the highly accurate positioning is paid more attentions. The ultra-wide band (UWB) receiver plays a crucial role in navigating the unmanned aerial vehicle (UAV) in indoor areas, because of its low cost and low power consumption. However, the positioning accuracy of UWB is drastically affected by the infamous multipath effect. Therefore, the Ultra Wideband (UWB)/Inertial Navigation System (INS) integrated indoor navigation is an effective approach to reduces the positioning errors. This paper proposes a tightly-coupled UWB/INS integration navigation based on factor graph optimization (FGO). For the loosely-coupled integration, the linear and nonlinear least square methods are employed to obtain the well-performed single point positioning. The Allan-variance analysis is used to estimate the process noise covariance of INS. Besides, to reduce the computational load of nonlinear optimization in factor graph, this paper employs the IMU preintegration factor. The location performance of the proposed FGO method is compared with an extended Kalman Filter (EKF). The results show that the proposed tightly-coupled UWB/INS integration method can realize the better positioning performance than that of the conventional EKF in Line-of-Sight (LOS) and NonLine-of-Sight (NLOS) combined indoor environments. (C) 2020 Elsevier Masson SAS. All rights reserved.

Automated summary

This paper proposes a tightly-coupled UWB/INS integration navigation method based on factor graph optimization to reduce positioning errors. Compared with the traditional Extended Kalman Filter (EKF), this method achieves better positioning performance in Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) combined indoor environments.