Title :
A Rao-Blackwellized particle filter for INS/GPS integration
Author :
Giremus, Audrey ; Doucet, Arnaud ; Calmettes, Vincent ; Tourneret, Jean-Yves
Author_Institution :
IRIT/ENSEEIHT/TeSA, Toulouse, France
Abstract :
The localization performance of a navigation system can be improved by coupling different types of sensors. The paper focuses on INS-GPS integration. INS and GPS measurements allow a non-linear state space model, which is appropriate to particle filtering, to be defined. This model being conditionally linear Gaussian, a Rao-Blackwellization procedure can be applied to reduce the variance of the estimates.
Keywords :
Global Positioning System; Monte Carlo methods; filtering theory; inertial navigation; parameter estimation; state-space methods; Global Positioning System; INS-GPS integration; Rao-Blackwellized filter; conditionally linear Gaussian model; estimation variance; inertial navigation systems; localization performance; navigation system; nonlinear filter; nonlinear state space model; particle filter; sequential Monte Carlo methods; Availability; Clocks; Extraterrestrial measurements; Global Positioning System; Inertial navigation; Particle filters; Particle measurements; Position measurement; Satellite navigation systems; State-space methods;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on
Print_ISBN :
0-7803-8484-9
DOI :
10.1109/ICASSP.2004.1326707
