Geo-Referencing of a Multi-Sensor System Based on Set-Membership Kalman Filter

authored by

Ligang Sun, Hamza Alkhatib, Jens André Paffenholz, Ingo Neumann

Abstract

In this paper, a novel set-membership Kalman filter is applied on a data set which is obtained from a real world experiment. In this experiment, taken from the scope of georeferencing of terrestrial laser scanner, a multi-sensor system has captured the trajectory of two GNSS antennas. The dynamical system contains the random uncertainty and set-membership uncertainty simultaneously. Both estimated results from classic extended Kalman filter and novel set-membership Kalman filter are shown and compared. Detailed analysis of the set-membership Kalman filter is given in the end.

Organisation(s)

Geodetic Institute

Type

Conference contribution

Pages

889-896

No. of pages

8

Publication date

05.09.2018

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Computer Vision and Pattern Recognition, Signal Processing, Statistics, Probability and Uncertainty, Instrumentation

Electronic version(s)

https://doi.org/10.23919/ICIF.2018.8455763 (Access: Closed)

 

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