Remote Sensing in Urban Positioning and Navigation

Dear Colleagues,

GNSS positioning is becoming a significant service in the field of automatic transformation (autonomous vehicles), yet GNSS tends to perform poorly in urban areas due to NLOS and multipath effects. Moreover, the vulnerability of GNSS to jamming and spoofing attacks emphasizes the need to have a reliable system for sensing the accuracy of the GNSS in positioning, velocity, and timing (PVT).

This Special Issue focuses on methods and techniques for sensing and surveying the positioning and the navigation performance of standard and RTK GNSS devices in an urban environment. In particular, the following related topics are within the scope of this Special Issue:

• Methods for approximating the expected PVT (positioning, velocity, and timing) accuracy in real time;
• Methods for surveying and mapping the expected performance of PVT in urban regions;
• Using crowd sourcing for detecting jamming and spoofing attacks in dense urban regions;
• Methods for improving the robustness of GNSS performance using both PPP and RTK;
• Machine learning and deep learning methods for classifying LOS and NLOS state for each signal (from each navigation satellite);
• Methods for performing raw GNSS surveying using smartphones;
• Methods for performing 3D drone navigation in urban regions with expected GNSS delay conditions (urban regions);
• Methods for combining L1, L2, L5 raw GNSS data of multi constellations for creating a more reliable and accurate PVT;
• Methods for predicting GNSS signal deterioration in urban navigation.

Prof. Dr. Boaz Ben-Moshe
Guest Editor

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