Authors:
Tom L. Koller
;
Tim Laue
and
Udo Frese
Affiliation:
Multi-Sensoric Systems, University of Bremen, Enrique-Schmidt-Str. 5, Bremen and Germany
Keyword(s):
State Estimation, Kalman Filter, Prior Knowledge, Inertial Navigation System (INS), State Observability.
Related
Ontology
Subjects/Areas/Topics:
Informatics in Control, Automation and Robotics
;
Sensors Fusion
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
Inertial Navigation Systems suffer from unbounded errors on the position and orientation estimate. Exteroceptive sensors may not always be available to correct the error. Applications in the literature overcome this problem by fusing IMU data with prior knowledge in an ad-hoc fashion. In different applications, various knowledge is available, which allows to correct the erroneous state estimate. In this position paper, we argue that the fusion of knowledge and inertial sensor data should be viewed as a paradigm and that the observability of systems with prior knowledge should be analysed theoretically. With a theoretical foundation, application design will be simplified and verifiable. We show methods to start the analysis and give a first proof with practical insight.