Signal Propagation Analysis And Signature Extraction For Gnss Indoor Positioning

The large popularization of GNSS (based on GPS, Glonass and forthcoming Galileo) receivers and the increased market interest for Location Based Services (LBS) have motivated interesting studies in modelling the radio channel propagation for dense urban and indoor geolocation, where two key problems need to be addressed: weak signal operation and multipath, both leading to receiver range errors and consequently position being calculated with large biases.In this paper we introduce a modified ray tracing radio frequency propagation approach, designed specially to follow the signal from GNSS space vehicles and accounting for all the physical characteristics of the indoor environment. This is achieved by the use of a computationally optimized semi-deterministic approach for radio propagation for moving transmitters. Exploiting the resulting GPS C/A code correlation curve distorted by the incidence of multipath, a signal deconvolution technique is applied to this distorted curve in order to identify multiple individual correlation curves that contribute to it. These deconvoluted individual curves are then stochastically analyzed, resulting in the extraction of corresponding signal "signatures", whose pattern is observed during a complete pass of the space vehicle. Due to the inherent repeatability of the GNSS satellites orbits, these signal propagation signatures in an indoor test bed also repeat themselves on a daily basis. These signatures are then combined in order to associate specific signal signatures with corresponding unique positions in the test bed.The results from these preliminary experiments will serve as baseline for the development of a novel signal propagation model to enable GNSS indoor positioning, which will rely on local, site-specific support (based on previous knowledge of the indoor environment). The results discussed in this paper relate to tests performed in a confined and controlled environment, and the most relevant output of this work is therefore its contribution to the development of innovative algorithms to be applied to GNSS receivers, aimed at developing robust positioning equipment, able to support Location Based Services with the accuracy and reliability demanded by this emerging market.