Multipath often represents the dominant error source in GNSS (Global Navigation Satellite System). As a consequence, several techniques have been proposed to mitigate its undesiredeffects, including Linear Adaptive Filters (LAFs). In this paper a Least Squares (LS) filter is applied to a post-correlation GNSS signal. The case study considers a Galileo signal. Since after the correlation the noise results not to be white, which violate one of the basic assumptions of LAF theory, the focus of this paper is on the analysis of the colored noise effects on the LAF performance. An analytical study is done, proved by simulation results.
Effects of Colored Noise in Linear Adaptive Filters Applied to GNSS Multipath Detection / Ugazio, Sabrina; LO PRESTI, Letizia. - DASIP:(2013), pp. 126-133. (Intervento presentato al convegno 2013 Conference on Design and Archtictures for Signal and Image Processing (DASIP), Cagliari, Italy, October 8-10, 2013 tenutosi a Cagliari, Italy nel 2013, October 8-10).
Effects of Colored Noise in Linear Adaptive Filters Applied to GNSS Multipath Detection
UGAZIO, SABRINA;LO PRESTI, Letizia
2013
Abstract
Multipath often represents the dominant error source in GNSS (Global Navigation Satellite System). As a consequence, several techniques have been proposed to mitigate its undesiredeffects, including Linear Adaptive Filters (LAFs). In this paper a Least Squares (LS) filter is applied to a post-correlation GNSS signal. The case study considers a Galileo signal. Since after the correlation the noise results not to be white, which violate one of the basic assumptions of LAF theory, the focus of this paper is on the analysis of the colored noise effects on the LAF performance. An analytical study is done, proved by simulation results.Pubblicazioni consigliate
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https://hdl.handle.net/11583/2543759
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