An USBL/DR Integrated Underwater Localization Algorithm Considering Variations of Measurement Noise Covariance

Jie Ma,Yifei Yu,Xiaodong Zhu,Yu Zhang

doi:10.1109/access.2022.3149831

Jie Ma, Yifei Yu + Show 2 more

Open Access

https://doi.org/10.1109/access.2022.3149831

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Abstract

Ultrashort baseline (USBL) positioning system is an important part of the integrated navigation for underwater vehicles. The single USBL positioning system has problems such as reduced accuracy of azimuth measurement due to target motion and large impact of small angular variations, especially in the region where the target is close to the conical boundary, that is, the low-elevation region. To improve the positioning accuracy of the USBL-based integrated navigation system, a tightly coupled USBL/Dead Reckoning (DR) integrated localization algorithm that considers the time varying characteristics of the measurement noise was proposed, and the filtering model of the algorithm was designed. The algorithm exploits the mechanism of the azimuth measurement covariance variation of the USBL system, constructs an adaptive measurement noise estimator for the USBL system, and applies it to the integration filtering of USBL/DR data. A nonlinear extended Kalman filtering (EKF) model was used to fuse the USBL positioning and dead reckoning trajectories. A number of simulation tests with different elevation angle settings were performed to compare the performance of the proposed algorithm with that of a conventional EKF for underwater localization. The test results reveal that the proposed algorithm can effectively reduce the positioning error caused by the change in the relative azimuth of the acoustic signal owing the motion of the mother ship and the motion of the underwater vehicle.

Highlights

With the development of exploitation of marine resources, underwater vehicles have been gradually applied in various fields such as large area surveys and deep-sea diving [1]
Multi-sensor fusion refers to that the measured positioning information coming from ultra-short baseline (USBL) is used to continuously correct the trajectory coming from Dead Reckoning (DR)
We found that the measurement noise magnitude of USBL in tightly-coupled integrated systems is closely related to the inclination angles of return signal by studying the measurement mechanism

Summary

INTRODUCTION

With the development of exploitation of marine resources, underwater vehicles have been gradually applied in various fields such as large area surveys and deep-sea diving [1]. Tightly-coupled integration directly combines the slant range and inclination angles of the USBL measurements with the DR solution to form a filtered positioning solution. We found that the measurement noise magnitude of USBL in tightly-coupled integrated systems is closely related to the inclination angles of return signal by studying the measurement mechanism. We aim to model this relation and apply it to estimate the measured noise covariance matrix This estimation is consistent with the property of the USBL system. This measurement noise estimator enables simple filter construction and efficient calculation This proposed algorithm has been analyzed using simulation data.

USBL POSITIONING SYSYEM MEASUREMENTS

MEASUREMENT NOISE

A NOVEL LOCALIZATION ALGORITHM

FILTER DESIGN

TEST RESULTS Test1

CONLIUSION