Abstract

It is well known by users of Portable Navigation Device (PND) and other GPS-based devices that positioning suffers from (local) significant decreases of accuracy in partially obscured environments like urbanized areas, where buildings (especially high buildings), trees or terrain block large portions of the sky. In such areas, GPS receiver performance is usually deteriorated by the reduced number of currently available satellite signals, as well as by introducing their multipath. That is why the GPS positioning in dense urban areas is unreliable, with low positioning accuracy, particularly in the cross-street direction if a street is surrounded by high buildings. This problem is crucial, especially in the context of solutions based on GPS receivers dedicated for users with special requirements. An example may be blind and/or visually impaired persons using the low cost Personal Navigation Devices to support their movement, when high precision positioning is required, especially in the context of emergency situations. The proposed approach for reaching formulated technical objectives consists of examining the feasibility of integrating existing mobile PND platforms with the next-generation combined open GPS-Galileo receiver module. In addition to the proposed adoption of the combined GPS/Galileo receiver module in the considered scheme, it is assumed to implement in the project two complementary optional innovations which should further improve positioning accuracy, namely: application of map-matching algorithms, which should eliminate not-possible positioning (users locations) in dense urban areas, e.g. building roofs, and application of information source fusion using Bayesian particle filtering algorithms - this seems to be especially promising when 3D spatial data is available, (e.g. city blocks or building 3D models), and when the filter can be fed with such a priori information.

Authors (3)