GNSS navigation is critical in unfavourable scenarios, where the solution can be degraded by errors such as multipath reflections and weak geometries caused by obstacles surrounding the receiver. Nonetheless, the influence of the errors can be reduced defining an adequate quality measure for each signal and, consequently, using weights inversely related to the quality of the received signals. In this paper, a quality index, obtained from the fuzzy integration of various features of the received signals and leveraged to weight each measure in a Weighted Least Square (WLS) estimation process, is validated on measurements coming from a High Sensitivity receiver embedded in a smartphone. The main objective is to validate a fuzzy control designer provided by the authors in a previous work using raw data from a smartphone to compute the navigation solution and to extend its application to the multi-GNSS constellation case. The performance of the tested weighting strategy is evaluated in the position domain and in comparison with another weighting method. GNSS real data have been collected through a smartphone located in typical urban canyon environment, and processed in Single Point Positioning. Results show an evident enhancement obtained from the application of the fuzzy logic to obtain a proper weight to be assigned to GNSS observables reproducing a stochastic model similar to the reality.
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