Geo-Referencing of a Multi-Sensor System Based on Set-Membership Kalman Filter
Ligang Sun, Hamza Alkhatib, Jens‐André Paffenholz, Ingo Neumann · 2018
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.