NDLI: Robust INS/GPS Sensor Fusion for UAV Localization Using SDRE Nonlinear Filtering

Content Provider	IEEE Xplore Digital Library
Author	Nemra, A. Aouf, N.
Copyright Year	2001
Abstract	The aim of this paper is to present a new INS/GPS sensor fusion scheme, based on state-dependent Riccati equation (SDRE) nonlinear filtering, for unmanned aerial vehicle (UAV) localization problem. SDRE navigation filter is proposed as an alternative to extended Kalman filter (EKF), which has been largely used in the literature. Based on optimal control theory, SDRE filter solves issues linked with EKF filter such as linearization errors, which severely decrease UAV localization performances. Stability proof of SDRE nonlinear filter is also presented and validated on a 3-D UAV flight scenario. Results obtained by SDRE navigation filter were compared to EKF navigation filter results. This comparison shows better UAV localization performance using SDRE filter. The suitability of the SDRE navigation filter over an unscented Kalman navigation filter for highly nonlinear UAV flights is also demonstrated.
Sponsorship	IEEE Sensors Council
Starting Page	789
Ending Page	798
Page Count	10
File Size	1373090
File Format	PDF
ISSN	1530437X
Volume Number	10
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-04-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robustness Global Positioning System Sensor fusion Unmanned aerial vehicles Filters Navigation Riccati equations Filtering theory Nonlinear equations Optimal control unmanned aerial vehicle (UAV) localization Sensor data fusion state-dependent Riccati equation (SDRE) nonlinear filter SDRE stability
Content Type	Text
Resource Type	Article
Subject	Instrumentation Electrical and Electronic Engineering

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