DocumentCode :
1606522
Title :
A framework for particle filtering in positioning, navigation and tracking problems
Author :
Gustafsson, F. ; Gunnarsson, F. ; Bergman, N. ; Forssell, U. ; Jansson, J. ; Nordlund, P.-J. ; Karlsson, R.
Author_Institution :
Dept. of Electr. Eng., Linkoping Univ., Sweden
fYear :
2001
fDate :
6/23/1905 12:00:00 AM
Firstpage :
34
Lastpage :
37
Abstract :
A framework for positioning, navigation and tracking problems using particle filters (recursive Monte Carlo methods) is developed. Automotive and airborne applications, approached in this framework, have proven a numerical advantage over classical Kalman filter based algorithms. Here the use of non-linear measurement models and non-Gaussian measurement noise is the main explanation for the improvement in accuracy, and models for relevant sensors are surveyed
Keywords :
Monte Carlo methods; aircraft navigation; filtering theory; inertial navigation; measurement errors; tracking filters; airborne applications; aircraft positioning; automotive applications; integrated navigation; navigation problems; nonGaussian measurement noise; nonlinear measurement models; particle filtering; positioning problems; recursive Monte Carlo methods; sensors; statistical signal processing; tracking problems; Equations; Filtering; Navigation; Noise measurement; Particle filters; Particle tracking; Position measurement; Sensor phenomena and characterization; Signal processing algorithms; Ultrasonic variables measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Statistical Signal Processing, 2001. Proceedings of the 11th IEEE Signal Processing Workshop on
Print_ISBN :
0-7803-7011-2
Type :
conf
DOI :
10.1109/SSP.2001.955215
Filename :
955215
Link To Document :
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