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Adaptive Kalman filtering based navigation: an IMU/GPS integration approach
Department of Electrical and Computer Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-0079-9049
Department of Electrical and Computer Engineering, Islamic Azad University.
2011 (English)In: Proceedings of the 8th IEEE International Conference on Networking, Sensing and Control: Delft, The Netherlands, 11-13 April, 2011, Piscataway, NJ: IEEE Communications Society, 2011, p. 181-185Conference paper, Published paper (Refereed)
Abstract [en]

This paper investigates on the development and implementation of a high integrity navigation system based on the combined use of the Global Positioning System (GPS) and an inertial measurement unit (IMU) for land vehicle applications. The complementary properties of the GPS and the INS have motivated several works dealing with their fusion by using a Kalman Filter. The conventional kalman filter has a fix error covariance matrix in all times of processing. Multi-sensor based navigation system that is implemented in this paper is called data synchronization. Also, multi-rate operations that are compared with conventional Kalman filtering has fix error covariance matrix. Therefore, when GPS outage occurred we have improper treat by kalman filter. In this paper we present an Adaptive method instead of conventional methods. It is shown that proposed method has a better performance rather than conventional method. Experimental results show the effectiveness of the GPS/INS integrated system.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Communications Society, 2011. p. 181-185
Keywords [en]
global positioning system (GPS), inertial measurement unit (IMU), Kalman filter, Land vehicle, navigation
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-34333DOI: 10.1109/ICNSC.2011.5874871Scopus ID: 2-s2.0-79959969911Local ID: 881e3448-edb6-4a20-9beb-dc8ab13465b6ISBN: 978-1-4244-9570-2 (print)OAI: oai:DiVA.org:ltu-34333DiVA, id: diva2:1007583
Conference
IEEE International Conference on Networking, Sensing and Control : 11/04/2011 - 13/04/2011
Note

Godkänd; 2011; 20110407 (tgu)

Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2022-10-12Bibliographically approved

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Fakharian, AhmadGustafsson, Thomas

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