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Proceedings Paper

On the consistency analysis of A-SLAM for UAV navigation
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Paper Abstract

Simultaneous Localization and Mapping (SLAM) is a good choice for UAV navigation when both UAV’s position and region map are not known. Due to nonlinearity of kinematic equations of a UAV, Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) are employed. In this study, EKF and UKF based A-SLAM concepts are discussed in details by presenting the formulations and simulation results. The UAV kinematic model and the state-observation models for EKF and UKF based A-SLAM methods are developed to analyze the filters' consistencies. Analysis during landmark observation exhibits an inconsistency in the form of a jagged UAV trajectory. It has been found that unobservable subspaces and the Jacobien matrices used for linearization are two major sources of the inconsistencies observed. UKF performs better in terms of filter consistency since it does not require the Jacobien matrix linearization.

Paper Details

Date Published: 3 June 2014
PDF: 12 pages
Proc. SPIE 9084, Unmanned Systems Technology XVI, 90840R (3 June 2014); doi: 10.1117/12.2053258
Show Author Affiliations
A. Ersan Oguz, Turkish Air Force Academy (Turkey)
Hakan Temeltas, Istanbul Technical Univ. (Turkey)


Published in SPIE Proceedings Vol. 9084:
Unmanned Systems Technology XVI
Robert E. Karlsen; Douglas W. Gage; Charles M. Shoemaker; Grant R. Gerhart, Editor(s)

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