DocumentCode :
3640077
Title :
Kalman filter-based architecture for robust and high-sensitivity tracking in GNSS receivers
Author :
José A. Del Peral-Rosado;José A. López-Salcedo;Gonzalo Seco-Granados;José M. López-Almansa;Joaquín Cosmen
Author_Institution :
Signal Processing for Communication and Navigation Group (SPCOMNAV), Universitat Autò
fYear :
2010
Firstpage :
1
Lastpage :
8
Abstract :
Blockage of the line-of-sight (LOS) component is one of the main problems of GNSS receivers when operating in harsh working conditions. This is the case, for instance, of urban canyons, where GNSS receivers in moving vehicles are subject to sudden fading events with more than 20 dB of signal attenuation. In these circumstances it is not possible for traditional receivers to keep track of the received signals, thus failing to provide reliable position fixes. The problem is aggravated when hardware implementation constraints need to be satisfied. For instance, as in target applications that involve embedding GNSS capabilities into ARM processors of mobile devices. Therefore, high-sensitivity GNSS receivers with reduced complexity and power consumption are mandatory. The contribution of this paper is the proposal and analysis with synthetic signal of a Kalman filter-based architecture for robust and high-sensitivity tracking. The use of extended correlations mitigates the measurement noise and allows the tracking operation under these harsh conditions. The results obtained validate the strategy proposed to operate at a C/N0 (carrier-to-noise ratio) as low as 15 dBHz.
Keywords :
"Kalman filters","Receivers","Global Navigation Satellite Systems","Computer architecture","Noise","Noise measurement","Correlation"
Publisher :
ieee
Conference_Titel :
Satellite Navigation Technologies and European Workshop on GNSS Signals and Signal Processing (NAVITEC), 2010 5th ESA Workshop on
ISSN :
2325-5439
Print_ISBN :
978-1-4244-8740-0
Electronic_ISBN :
2325-5455
Type :
conf
DOI :
10.1109/NAVITEC.2010.5708005
Filename :
5708005
Link To Document :
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