Satellite navigation is critical in signal-degraded environments such as urban canyons and mountainous area, where many GNSS signals are blocked by natural and artificial obstacles or are strongly degraded. Hence standalone GPS is often unable to guarantee a continuous and accurate positioning. A suitable approach could be the integration of several GNSS. Multi-constellation system guarantees an improved satellite availability with respect to GPS standalone, providing a positioning enhancement in terms of accuracy, continuity and integrity. Currently the ideal candidate for supplement GPS in a multi-constellation approach is the Russian GLONASS. The main purposes of this work are the performance assessment of a GNSS multi-constellation relative to GPS stand-alone and the comparison of Least Squares and Kalman Filter.

Algorithms for GNSS Positioning in Difficult Scenario

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2011

Abstract

Satellite navigation is critical in signal-degraded environments such as urban canyons and mountainous area, where many GNSS signals are blocked by natural and artificial obstacles or are strongly degraded. Hence standalone GPS is often unable to guarantee a continuous and accurate positioning. A suitable approach could be the integration of several GNSS. Multi-constellation system guarantees an improved satellite availability with respect to GPS standalone, providing a positioning enhancement in terms of accuracy, continuity and integrity. Currently the ideal candidate for supplement GPS in a multi-constellation approach is the Russian GLONASS. The main purposes of this work are the performance assessment of a GNSS multi-constellation relative to GPS stand-alone and the comparison of Least Squares and Kalman Filter.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11367/19303
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