Gunawan, BA; Liu, Y; Li, X; (2020) Adaptive Localisation for Unmanned Surface Vehicles Using IMU-Interacting Multiple Model. In: Proceedings of the 2020 International Conference on System Science and Engineering (ICSSE). IEEE: Kagawa, Japan.

Preview

Text ICSSE 2020 - Revision.pdf - Accepted Version Download (718kB) | Preview

Abstract

Unscented Kalman Filter (UKF) remains to be a prevalent multi-sensor fusion method in many practices, including navigational tracking for Unmanned Surface Vehicles (USVs). This paper suggests that results from UKF fusion is unsatisfactory for USVs’ relatively smooth path due to UKF’s lack of versatility. Hence, it is proposed here that by replacing the UKF with Interacting Multiple Model (IMM), estimation results will better represent USV’s movement. Furthermore, this paper proposes slight modification to the IMM in order to heighten the algorithm’s confidence in switching modes. By exploiting angular velocity information from Inertial Measurement Unit (IMU), an independent mode probability can be obtained which is then injected into the IMM. Computer simulations based on maritime operations were done to show that the proposed IMU-based IMM is able to react faster to mode changes, giving more reliable outcomes.

Download activity - last month

Export as CSVJSONXML

Download activity - last 12 months

Export as CSVXMLJSON

Downloads by country - last 12 months

Export as XMLJSONCSV

Archive Staff Only

View Item