Limiting the weight of bad signals can recover the accuracy of the GNSS solution in signal-degraded scenarios, where multipath reflections and obstructions can easily generate multiple blunders. The fuzzy integration of the available information related to the quality of the received signals is exploited in this paper to derive an effective weighting schema in a Weighted Least Square estimation process. To validate the proposed schema, its performance in the position domain is compared to the most common weighting strategies proposed in the literature, based on GPS data collected through two different High Sensitivity GNSS receivers placed in urban canyons and processed in Single Point Positioning using pseudorange measurements.
Fuzzy logic applied to GNSS
Gaglione, Salvatore;Angrisano, Antonio;Innac, Anna
;Del Pizzo, Silvio;Maratea, Antonio
2019-01-01
Abstract
Limiting the weight of bad signals can recover the accuracy of the GNSS solution in signal-degraded scenarios, where multipath reflections and obstructions can easily generate multiple blunders. The fuzzy integration of the available information related to the quality of the received signals is exploited in this paper to derive an effective weighting schema in a Weighted Least Square estimation process. To validate the proposed schema, its performance in the position domain is compared to the most common weighting strategies proposed in the literature, based on GPS data collected through two different High Sensitivity GNSS receivers placed in urban canyons and processed in Single Point Positioning using pseudorange measurements.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
