An Improved Unscented Kalman Filter Applied to Positioning and Navigation of Autonomous Underwater Vehicles

An Improved Unscented Kalman Filter Applied to Positioning and Navigation of Autonomous Underwater Vehicles

To enhance the positioning accuracy of autonomous underwater vehicles (AUVs), a new adaptive filtering algorithm (RHAUKF) is proposed. The most widely used filtering algorithm is the traditional Unscented Kalman Filter or the Adaptive Robust UKF (ARUKF). Excessive noise interference may cause a decr...

Full description

Saved in:
Bibliographic Details
Main Authors: Jinchao Zhao, Ya Zhang, Shizhong Li, Jiaxuan Wang, Lingling Fang, Luoyin Ning, Jinghao Feng, Jianwu Zhang
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Sensors
Subjects:
unscented Kalman filter
inertial navigation system
unmanned underwater vehicle
integrated navigation
Online Access:https://www.mdpi.com/1424-8220/25/2/551
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items