In the rapidly evolving landscape of urban development, the demand for precise and intelligent positioning systems has become paramount. Navigating through densely populated urban environments requires advanced technologies that go beyond traditional GPS solutions. This article delves into the realm of Intelligent Urban Positioning, exploring the integration of Multi-GNSS with cutting-edge 3D mapping technologies.

Background
Intelligent Urban Positioning (IUP) strives to attain precise and accurate object or individual positioning within urban environments through the utilization of advanced technologies and systems. The term encompasses the integration of various technologies to overcome challenges in densely populated and complex urban landscapes. Achieving reliable meters-level positioning in such areas proves challenging and cost-effective with a singular method. The solution lies in amalgamating multiple positioning techniques, and Intelligent Urban Positioning (IUP) aims to achieve this enhanced performance by combining three key ingredients:

Multi-constellation GNSS;
Detection of non-line-of-sight (NLOS) signal propagation;
Three-dimensional mapping.
Urban Positioning Challenges
The urban environment presents two major challenges to GNSS signal reception. Firstly, the buildings and other obstacles, such as buses, block the direct line-of-sight (LOS) to many of the satellites, effectively reducing the number in view. Consequently, a multi-constellation receiver is essential in order to reliably obtain sufficient direct-LOS signals to compute a position solution. At many urban locations, a full global deployment of all four GNSS constellations will be required for a high positionsolution availability.

Due to the obstruction of signals from buildings across the street, only signals along the street remain, resulting in suboptimal geometry for position solutions. This leads to a significant increase in dilution of precision across the street compared to along the street, consequently causing lower accuracy in the cross-street direction, as depicted in Figure 1.

more reference: https://www.ericcointernational.com/application/intelligent-urban-positioning-using-multi-gnss-with-3d-mapping.html