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GNSS-aided INS for land vehicle positioning and navigation
KTH, School of Electrical Engineering (EES), Signal Processing.ORCID iD: 0000-0002-3054-6413
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: urn:nbn:se:kth:diva-4556OAI: oai:DiVA.org:kth-4556DiVA: diva2:12840
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
List of papers
1. In-Car Positioning and Navigation Technologies: a survey
Open this publication in new window or tab >>In-Car Positioning and Navigation Technologies: a survey
2009 (English)In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 10, no 1, 4-21 p.Article, review/survey (Refereed) Published
Abstract [en]

In-car positioning and navigation has been a killer application for Global Positioning System (GPS) receivers, and a variety of electronics for consumers and professionals have been launched on a large scale. Positioning technologies based on stand-alone GPS receivers are vulnerable and, thus, have to be supported by additional information sources to obtain the desired accuracy, integrity, availability, and continuity of service. A survey of the information sources and information fusion technologies used in current in-car navigation systems is presented. The pros and cons of the four commonly used information sources, namely, 1) receivers for radio-based positioning using satellites, 2) vehicle motion sensors, 3) vehicle models, and 4) digital map information, are described. Common filters to combine the information from the various sources are discussed. The expansion of the number of satellites and the number of satellite systems, with their usage of available radio spectrum, is an enabler for further development, in combination with the rapid development of microelectromechanical inertial sensors and refined digital maps.

Keyword
Dead reckoning (DR), Inertial navigation, Information fusion, Satellite navigation, Vehicle models, Vehicle navigation
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-7724 (URN)10.1109/TITS.2008.2011712 (DOI)000263919800002 ()2-s2.0-61849182591 (Scopus ID)
Note
Uppdaterad från submitted till published(20101116) QC 20101116Available from: 2007-11-25 Created: 2007-11-25 Last updated: 2011-11-15Bibliographically approved
2. A low-cost GPS aided inertial navigation system for vehicle applications
Open this publication in new window or tab >>A low-cost GPS aided inertial navigation system for vehicle applications
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.

National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-7725 (URN)2-s2.0-84863650887 (Scopus ID)978-160423821-1 (ISBN)
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
3. A versatile PC-based platform for inertial navigation
Open this publication in new window or tab >>A versatile PC-based platform for inertial navigation
2007 (English)In: Proceedings of the 7th Nordic Signal Processing Symposium, NORSIG 2006, New York: IEEE , 2007, 262-265 p.Conference paper, Published paper (Refereed)
Abstract [en]

A GPS aided inertial navigation platform is presented, into which further sensors such as a camera, wheel-speed encoder etc., can be incorporated. The construction of the platform is described and an introduction to the sensor fusion approach is given. Results from a field-test is presented, indicating which error sources that needs to be modelled more accurately.

Place, publisher, year, edition, pages
New York: IEEE, 2007
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-7726 (URN)10.1109/NORSIG.2006.275238 (DOI)000245415000067 ()2-s2.0-39049127990 (Scopus ID)978-142440412-4 (ISBN)
Conference
7th Nordic Signal Processing Symposium, NORSIG 2006; Reykjavik; 7 June 2006 through 9 June 2006
Note
QC 20101116Available from: 2007-11-25 Created: 2007-11-25 Last updated: 2010-11-16Bibliographically approved
4. Calibration of a MEMS inertial measurement unit
Open this publication in new window or tab >>Calibration of a MEMS inertial measurement unit
2006 (English)In: Proc. XVII IMEKO World Congress, (Rio de Janeiro, Brazil), Sept.2006, 2006Conference paper, Published paper (Refereed)
Abstract [en]

An approach for calibrating a low-cost IMU isstudied, requiring no mechanical platform for the accelerometercalibration and only a simple rotating table for the gyrocalibration. The proposed calibration methods utilize the factthat ideally the norm of the measured output of the accelerometerand gyro cluster are equal to the magnitude of appliedforce and rotational velocity, respectively. This fact, togetherwith model of the sensors is used to construct a cost function,which is minimized with respect to the unknown model parametersusing Newton’s method. The performance of the calibrationalgorithm is compared with the Cram´er-Rao bound forthe case when a mechanical platform is used to rotate the IMUinto different precisely controlled orientations. Simulation resultsshows that the mean square error of the estimated sensormodel parameters reaches the Cram´er-Rao bound within8 dB, and thus the proposed method may be acceptable for awide range of low-cost applications.

Keyword
Inertial measurement unit, MEMS sensors, Calibration
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-7727 (URN)2-s2.0-84877782606 (Scopus ID)978-162276646-8 (ISBN)
Conference
XVII IMEKO World Congress, (Rio de Janeiro, Brazil), 17-22 September 2006
Note

QC 20141105

Available from: 2007-11-25 Created: 2007-11-25 Last updated: 2014-11-05Bibliographically approved
5. Time Synchronization Errors in Loosely Coupled GPS-Aided Inertial Navigation Systems
Open this publication in new window or tab >>Time Synchronization Errors in Loosely Coupled GPS-Aided Inertial Navigation Systems
2011 (English)In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 12, no 4, 1014-1023 p.Article in journal (Refereed) Published
Abstract [en]

The effects of data time synchronization errors in a loosely coupled Global-Positioning-System (GPS)-aided inertial navigation system (INS) are studied and quantified in terms of the increased mean square error (MSE) of the navigation solution. An expression for evaluating the MSE of the navigation solution, given the vehicle trajectory and the model of the INS error dynamics, is derived. Thereafter, a software-based time synchronization method, where the time synchronization error is included as a state to be estimated by the data integration filter, is proposed. A practical approach to the implementation of the proposed time synchronization method is also briefly described. Moreover, an expression for the MSE of the navigation solution in the system that employs the proposed synchronization method is derived. Finally, through simulations and tests with real-world data, the correctness of the derived MSE expressions is validated, and the application of the proposed synchronization method is shown. The test results show that, with the proposed synchronization approach, a data time synchronization, which is accurate to the order of a few milliseconds, can be achieved.

Keyword
Global Positioning System (GPS), inertial navigation system (INS), integrated navigation, time synchronization
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-55247 (URN)10.1109/TITS.2011.2126569 (DOI)000297588500007 ()2-s2.0-82455212058 (Scopus ID)
Funder
EU, European Research Council, 228044
Note
QC 20120109Available from: 2012-01-09 Created: 2012-01-02 Last updated: 2017-12-08Bibliographically approved

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