Unscented kalman filter with process noise covariance estimation for vehicular ins/gps integration system-Reference-Cited by-同舟云学术

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Unscented kalman filter with process noise covariance estimation for vehicular ins/gps integration system

Published:2020-12 Issue: Volume:64 Page:194-204
ISSN:1566-2535
Container-title:Information Fusion
language:en
Short-container-title:Information Fusion

Author:

Hu Gaoge,Gao Bingbing,Zhong Yongmin,Gu Chengfan

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Hardware and Architecture,Information Systems,Signal Processing,Software

Reference37 articles.

1. Principles of GPS, Inertial, and Multisensor Integrated Navigation Systems;Groves P,2008

2. A derivative UKF for tightly coupled INS/GPS integrated navigation;Hu G;ISA Trans,2015

3. Zhong YM .et al. A new direct filtering approach to INS/GNSS integration;Hu G;Aerospace Science and Technology,2018

4. GPS/INS integration utilizing dynamic neural networks for vehicular navigation;Noureldin;Information Fusion,2011

5. An innovative information fusion method with adaptive Kalman filter for integrated INS/GPS navigation of autonomous vehicles;Liu Y;Mech Syst Signal Process,2018

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