Title :
Based on the channel estimation Kalman filtering performance analysis
Author :
Caiwu Wang ; Jiang Chang ; Shiwei Tian
Author_Institution :
Coll. of Commun. Eng., PLA Univ. of Sci. & Technol., Nanjing, China
Abstract :
Kalman filter the optimal operation need the outside world to provide filter process noise variance Q and measurement noise variance R is accurate, otherwise Kalman gain and state estimate and parameter will not achieve their optimal value, even may cause filter divergence. This paper first shows the advantages of Kalman. And by using the experience of estimated parameter method and channel for carrier to noise ratio monitoring estimate R parameter, at The last experience estimation given R matrix Kalman filtering in the navigation positioning under application results were compared.
Keywords :
Global Positioning System; Kalman filters; channel estimation; R-matrix Kalman filtering; carrier-to-noise ratio monitoring estimate R-parameter; channel estimation Kalman filtering performance analysis; filter divergence; filter process noise variance Q-parameter; measurement noise variance R-parameter; navigation positioning; state estimation; Kalman filter; R matrix; carrier to noise ratio monitoring; experience estimation; style;
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4673-2963-7
DOI :
10.1109/ICCSNT.2012.6526008