Enhancement of Positioning and Attitude Estimation Using Raw GPS Data in an Extended Kalman Filter

University essay from Linköpings universitet/ReglerteknikLinköpings universitet/Tekniska högskolan


A Global Positioning System (GPS) can be used to estimate an objects position,given that the object has a GPS antenna. However, the system requires informationfrom at least four independent satellites in order to be able to give a positionestimate. If two GPS antennas and a carrier-phase GPS measurement unit is usedan estimate of the objects heading can be calculated by determine the baselinebetween the two antennas. The method is called GPS Attitude Determination(GPSAD) and requires that an Integer Ambiguity Problem (IAP) is solved. Thismethod is cheaper than more traditional methods to calculate the heading butis dependent on undisturbed GPS-reception. Through support from an InertialMeasurement Unit (IMU), containing accelerometers and gyroscopes, the systemcan be enhanced. In Thorstenson [2012] data from GPS, GPSAD and IMU wasintegrated in an Extended Kalman Filter (EKF) to enhance the performance. Thisthesis is an extension on Thorstensons work and is divided into two separate problems:enhancement of positioning when less than four satellites are available andthe possibility to integrate the EKF with the search of the correct integers for theIAP in order to enhance the estimation of attitude. For both problems an implementationhas been made and the performance has been enhanced for simulateddata. For the first problem it has been possible to enhance the performance onreal data while that has not been possible for the second problem. A number ofproposals is given on how to enhance the performance for the second problemusing real data.

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