Premium
The iterated extended set membership filter applied to relative localization between autonomous vehicles based on GNSS and UWB ranging
Author(s) -
Bolting Jan,
Fergani Soheib
Publication year - 2019
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.2206
Subject(s) - filter (signal processing) , ranging , computer science , parametric statistics , control theory (sociology) , iterated function , ellipsoid , gnss applications , set (abstract data type) , position (finance) , novelty , algorithm , mathematical optimization , mathematics , global positioning system , artificial intelligence , computer vision , geography , telecommunications , statistics , mathematical analysis , control (management) , geodesy , finance , economics , programming language , philosophy , theology
This paper presents a novel Iterated Extended Set Membership Filter (IESMF) with an application to relative localization. For safe operation of formations of automatic vehicles, consistent uncertainty estimates are of crucial importance. Here, a localization filter that provides ellipsoidal regions that are guaranteed to contain another vehicles position is presented. The proposed iterative update step can appreciably reduce the size of the a posteriori state ellipsoid. The idea of using SIVIA as a baseline to quantify conservativeness is introduced. Another novelty is that we take into account parametric uncertainty of the observation equation. The proposed filter is applied to a two unmanned aircraft systems (UAS) localization problem in simulation with observation noise obtained from real sensors. Simulation results illustrate the effective reduction of filter conservativeness by a small number of iterative updates.