A compensation method for gyroscope random drift based on unscented Kalman filter and support vector regression optimized by adaptive beetle antennae search algorithm-Reference-Cited by-同舟云学术

A compensation method for gyroscope random drift based on unscented Kalman filter and support vector regression optimized by adaptive beetle antennae search algorithm

Published:2022-06-07 Issue:4 Volume:53 Page:4350-4365
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Wang Pengfei,Li Guangchun,Gao Yanbin

Funder

Chongqing Municipal Education Commission Foundation

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

https://link.springer.com/content/pdf/10.1007/s10489-022-03734-7.pdf

Reference42 articles.

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3. Guang X, Gao Y, Leung H, Liu P, Li G (2018) An autonomous vehicle navigation system based on inertial and visual sensors. Sensors 18(9). https://doi.org/10.3390/s18092952

4. Chen J, Zhou B, Bao S, Liu X, Gu Z, Li L, Zhao Y, Zhu J, Lia Q (2021) A data-driven inertial navigation/bluetooth fusion algorithm for indoor localization. IEEE Sensors J, 1–1. https://doi.org/10.1109/JSEN.2021.3089516

5. Shang K, Lei M, Xiang Q, Na Y, Zhang L (2021) Tactical-grade interferometric fiber optic gyroscope based on an integrated optical chip. Opt Commun 485:126729. https://doi.org/10.1016/j.optcom.2020.126729

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