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A low-cost GPS aided inertial navigation system for vehicle applications
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-3054-6413
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-2718-0262
2005 (English)Conference paper, Published paper (Refereed)
Abstract [en]

In this paper an approach for integration between GPS and inertial navigation systems (INS) is described. The continuous-time navigation and error equations for an earth-centered earth-fixed INS system are presented. Using zero order hold sampling, the set of equations is discretized. An extended Kalman filter for closed loop integration between the GPS and INS is derived. The filter propagates and estimates the error states, which are fed back to the INS for correction of the internal navigation states. The integration algorithm is implemented on a host PC, which receives the GPS and inertial measurements via the serial port from a tailor made hardware platform, which is briefly discussed. Using a battery operated PC the system is fully mobile and suitable for real-time vehicle navigation. Simulation results of the system are presented.

Place, publisher, year, edition, pages
2005. 1007-1010 p.
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-7725Scopus ID: 2-s2.0-84863650887ISBN: 978-160423821-1 (print)OAI: oai:DiVA.org:kth-7725DiVA: diva2:12836
Conference
13th European Signal Processing Conference, EUSIPCO 2005; Antalya; Turkey; 4 September 2005 through 8 September 2005
Note

Qc 20101116

Available from: 2007-11-25 Created: 2007-11-25 Last updated: 2014-09-30Bibliographically approved
In thesis
1. GNSS-aided INS for land vehicle positioning and navigation
Open this publication in new window or tab >>GNSS-aided INS for land vehicle positioning and navigation
2007 (English)Licentiate thesis, comprehensive summary (Other scientific)
Abstract [en]

This thesis begins with a survey of current state-of-the art in-car navigation systems. The pros and cons of the four commonly used information sources — GNSS/RF-based positioning, vehicle motion sensors, vehicle models and map information — are described. Common filters to combine the information from the various sources are discussed.

Next, a GNSS-aided inertial navigation platform is presented, into which further sensors such as a camera and wheel-speed encoder can be incorporated. The construction of the hardware platform, together with an extended Kalman filter for a closed-loop integration between the GNSS receiver and the inertial navigation system (INS), is described. Results from a field test are presented.

Thereafter, an approach is studied for calibrating a low-cost inertial measurement unit (IMU), requiring no mechanical platform for the accelerometer calibration and only a simple rotating table for the gyro calibration. The performance of the calibration algorithm is compared with the Cramér-Rao bound for cases where a mechanical platform is used to rotate the IMU into different precisely controlled orientations.

Finally, the effects of time synchronization errors in a GNSS-aided INS are studied in terms of the increased error covariance of the state vector. Expressions for evaluating the error covariance of the navigation state vector are derived. Two different cases are studied in some detail. The first considers a navigation system in which the timing error is not taken into account by the integration filter. This leads to a system with an increased error covariance and a bias in the estimated forward acceleration. In the second case, a parameterization of the timing error is included as part of the estimation problem in the data integration. The estimated timing error is fed back to control an adjustable fractional delay filter, synchronizing the IMU and GNSS-receiver data.

Place, publisher, year, edition, pages
Stockholm: KTH, 2007. vii,[7] p.
Series
Trita-EE, ISSN 1653-5146 ; 2007:066
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-4556 (URN)
Presentation
2007-12-07, Hörsal E32, KTH, Lindstedtsvägen 3, Stockholm, 10:00
Opponent
Supervisors
Note
QC 20101117Available from: 2007-11-25 Created: 2007-11-25 Last updated: 2012-03-28Bibliographically approved

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Skog, IsaacHändel, Peter

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Citation style
  • apa
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  • ieee
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Output format
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