TY - JOUR
T1 - Loosely Coupled GNSS and IMU Integration for Accurate i-Boat Horizontal Navigation
AU - Cahyadi, M. N.
AU - Asfihani, T.
AU - Mardiyanto, R.
AU - Erfianti, R.
N1 - Publisher Copyright:
© Geoinformatics International.
PY - 2022/6
Y1 - 2022/6
N2 - Global Navigation Satellite System (GNSS) has been widely utilized as a navigation solution for a mobile vehicle, yet stand-alone GNSS is unable to achieve sufficient accuracy in some applications. For example, in aquatic environment, the accuracy position of Unmanned Surface Vehicle (USV) is affected by the wind, current, and waves dynamics. In this case, the integration of GNSS and Inertial Measurement Unit (IMU) is an approach that can be used to support USV localization to achieve an accurate navigation solution. This study integrates GNSS and IMU using Extended Kalman Filter (EKF) to process loosely coupled integration. The integration results show that the estimated x-position is 0.3058 m accurately and the y-position has an accuracy of 0.2780 m. Then, the loosely coupled integration results of EKF were compared with Unscented Kalman Filter (UKF) simulation in the previous studies. The integration of GNSS and IMU using EKF produces a higher RMSE value of 2D position and attitude angle than UKF Scenario I. However, due to the smoothing process, EKF can provide a visually smoother trajectory than UKF, although it has a significant difference from the observed trajectory. On the other hand, the linear velocity estimated by EKF shows better stability compared to UKF in both Scenario I and II.
AB - Global Navigation Satellite System (GNSS) has been widely utilized as a navigation solution for a mobile vehicle, yet stand-alone GNSS is unable to achieve sufficient accuracy in some applications. For example, in aquatic environment, the accuracy position of Unmanned Surface Vehicle (USV) is affected by the wind, current, and waves dynamics. In this case, the integration of GNSS and Inertial Measurement Unit (IMU) is an approach that can be used to support USV localization to achieve an accurate navigation solution. This study integrates GNSS and IMU using Extended Kalman Filter (EKF) to process loosely coupled integration. The integration results show that the estimated x-position is 0.3058 m accurately and the y-position has an accuracy of 0.2780 m. Then, the loosely coupled integration results of EKF were compared with Unscented Kalman Filter (UKF) simulation in the previous studies. The integration of GNSS and IMU using EKF produces a higher RMSE value of 2D position and attitude angle than UKF Scenario I. However, due to the smoothing process, EKF can provide a visually smoother trajectory than UKF, although it has a significant difference from the observed trajectory. On the other hand, the linear velocity estimated by EKF shows better stability compared to UKF in both Scenario I and II.
UR - http://www.scopus.com/inward/record.url?scp=85133804608&partnerID=8YFLogxK
U2 - 10.52939/ijg.v18i3.2233
DO - 10.52939/ijg.v18i3.2233
M3 - Article
AN - SCOPUS:85133804608
SN - 1686-6576
VL - 18
SP - 111
EP - 122
JO - International Journal of Geoinformatics
JF - International Journal of Geoinformatics
IS - 3
ER -