Optimal nonlinear filtering in GPS/INS integration

Author

Carvalho, H. ; Del Moral, P. ; Monin, A. ; Salut, G.

Author_Institution

Lab. d´´Autom. et d´´Anal. des Syst., CNRS, Toulouse, France

Volume

33

Issue

3

fYear

1997

fDate

7/1/1997 12:00:00 AM

Firstpage

835

Lastpage

850

Abstract

The application of optimal nonlinear/non-Gaussian filtering to the problem of INS/GPS integration in critical situations is described. This approach is made possible by a new technique called particle filtering, and exhibits superior performance when compared with classical suboptimal techniques such as extended Kalman filtering. Particle filtering theory is introduced and GPS/INS integration simulation results are discussed.

Keywords

Bayes methods; Global Positioning System; adaptive estimation; aerospace computing; discrete time filters; filtering theory; inertial navigation; nonlinear filters; observability; recursive estimation; state-space methods; Bayes correction; GPS/INS integration; Radon-Nykodim derivative; conditional probability; critical situations; discrete-time filtering; navigation filter; non-Gaussian filtering; optimal nonlinear filtering; particle filtering; random variables; recalibration; regularizing function; simulation; state space; Ethics; Filtering theory; Global Positioning System; Inertial navigation; Kalman filters; Particle measurements; Satellite navigation systems; Satellites; Stochastic processes; Uninterruptible power systems; Vehicles; Weight measurement;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/7.599254

Filename

599254