Paper Info
Title
Design of a navigation filter by analysis of local observability
Abstract
This paper presents an inertial navigation filter designed for an automotive vehicle not equipped with any GPS receiver. The task of this filter is to provide relative position information over a relatively long period of time (tens of minutes). The filter consists of several partial state observers that, one after another, reconstruct key information for the whole state estimation. The observer relies on a sufficient condition to guarantee uniform complete observability of a general bounded linear time-varying system using (point-wise) differential rank conditions. From this condition, we construct a collection of filters well-suited for each possible trajectory of the vehicle. This results in temporally interconnected observers which are of the Kalman filter type. It is proven that each of them asymptotically converges to zero. We illustrate this design with trajectory estimation obtained on simulation data. Finally, experimental results using low-cost sensors show the potential and the relevance of the approach.
Year
DOI
Venue
2010
10.1109/CDC.2010.5717848
CDC
Keywords
Field
DocType
Kalman filters,inertial navigation,linear systems,observability,observers,road vehicles,time-varying systems,Kalman filter,automotive vehicle,bounded linear time-varying system,differential rank condition,inertial navigation filter,local observability analysis,observability,partial state observer,relative position information,state estimation,trajectory estimation
Inertial navigation system,Extended Kalman filter,Observability,Alpha beta filter,Control theory,Computer science,Kalman filter,Global Positioning System,Observer (quantum physics),Filter design
Conference
ISSN
Citations 
PageRank 
0743-1546
4
0.62
References 
Authors
3
3
Name
Order
Citations
PageRank
Pierre-Jean Bristeau1223.78
Nicolas Petit2223.78
Praly, L.31835364.39