Title: Online calibration of ultra-short baseline installation error in dynamic environment

Authors: Liang Zhang; Tao Zhang; Jinwu Tong; Shaoen Wu

Addresses: School of Instrument Science and Engineering, Southeast University, Nanjing, 210096, China ' School of Instrument Science and Engineering, Southeast University, Nanjing, 210096, China ' School of Instrument Science and Engineering, Southeast University, Nanjing, 210096, China ' Department of Computer Science, Ball State University, Muncie, 47302, USA

Abstract: The ultra-short base-line system is widely used in the navigation of ships and underwater vehicles. The installation error between the sensor and inertial measurement unit (IMU) are the main sources of positioning inaccuracy. In high-precision navigation, the installation error is not negligible. A method based on Kalman filter is designed to estimate the installation error of USBL in real time. The detailed derivation of Kalman filter for the calibration is presented in the paper. Then the observability analysis is carried out to verify the feasibility of the method. Simulation results show that the method proposed in this paper can calibrate the installation error between the ultra-short baseline and inertial measurement unit in real time and online. The positioning accuracy is improved by compensating the installation error. Therefore, the error calibration method proposed in this paper is effective and can greatly improve the positioning accuracy of USBL.

Keywords: error calibration; Kalman filter; ultra-short baseline; observability analysis; underwater navigation.

DOI: 10.1504/IJSNET.2019.101243

International Journal of Sensor Networks, 2019 Vol.30 No.4, pp.254 - 262

Received: 19 Feb 2019
Accepted: 02 Apr 2019
Published online: 29 Jul 2019 *

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