FIG Peer Review Journal


Adaptive Extended Kalman Filter for Geo-Referencing of a TLS-based Multi-Sensor-System (4052)

Jens-André Paffenholz, Hamza Alkhatib and Hansjörg Kutterer (Germany)
Mr. Jens-André Paffenholz
Geodetic Institute
Leibniz Universität Hannover
Nienburger Str. 1
Corresponding author Mr. Jens-André Paffenholz (email: paffenholz[at], tel.: + 49 511 7623191)

[ abstract ] [ paper ] [ handouts ]

Published on the web 2010-01-14
Received 2009-11-19 / Accepted 2010-01-14
This paper is one of selection of papers published for the FIG Congress 2010 in Sydney, Australia and has undergone the FIG Peer Review Process.

FIG Congress 2010
ISBN 978-87-90907-87-7 ISSN 2308-3441


This paper works on an adaptive extended Kalman filter (AEKF) approach for geo-referencing tasks for a multi-sensor system (MSS). The MSS is built up by a sensor fusion of a phase-based terrestrial laser scanner (TLS) with navigation sensors such as, e.g., Global Navigation Satellite System (GNSS) equipment and inclinometers. The position and orientation of the MSS are the main parameters which are derived by a Kalman filtering process. However, by inclinometer measurements the spatial rotation angles about the X- and Y-axis of the MSS can be respected in the AEKF. This makes it possible to respect all 6 degrees of freedom of the transformation from a sensor-defined to a global coordinate system. The paper gives a detailed discussion of the strategy for the direct geo-referencing. The AEKF for the transformation parameters estimation is presented with the focus on the modeling of the MSS motion. The potential of the strategy will be shown by practical investigations as well as an overview about the observation and GNSS analysis strategy will be given.
Keywords: GNSS/GPS; Positioning; Laser scanning; extended Kalman filter