Beidou navigation method based on intelligent computing and extended Kalman filter fusion-Reference-Cited by-同舟云学术

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Beidou navigation method based on intelligent computing and extended Kalman filter fusion

Published:2018-11-10 Issue:11 Volume:10 Page:4431-4438
ISSN:1868-5137
Container-title:Journal of Ambient Intelligence and Humanized Computing
language:en
Short-container-title:J Ambient Intell Human Comput

Author:

Tang Yongwei,Zhao Jingbo,Wang Maoli,Hao Huijuan,He Xiaoning,Meng Yuxiao

Funder

National key research and development plan

Shandong province natural science foundation of China

Innovation plan of agricultural machinery and equipment in Shandong province

Shandong agricultural machinery innovation plan

Publisher

Springer Science and Business Media LLC

Subject

General Computer Science

Link

http://link.springer.com/content/pdf/10.1007/s12652-018-1124-5.pdf

Reference13 articles.

1. Abayazid M, Roesthuis RJ, Reilink R, Misra S (2013) Integrating deflection models and image feedback for real-time flexible needle steering. IEEE Trans Rob 29(2):542–553

2. Anderson R, Bevly DM (2010) Using GPS with a model-based estimator to estimate critical vehicle states. Veh Syst Dyn 48(12):1413–1438

3. Barrio R, Rodriguez M, Abad A, Blesa F (2011) Breaking the limits: the Taylor series method. Appl Math Comput 217(20):7940–7954

4. Caron FE, Duflos D, Pomorski P Vanheeghe (2017) GPS/IMU data fusion using multisensor Kalman filtering: introduction of contextual aspects. Inform Fusion 7(2):221–230

5. Harko T, Leung CS, Mocanu G (2014) Generalized Langevin equation with colored noise description of the stochastic oscillations of accretion disks. Euro Phys J C 74(5):1–16

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