Abstract
3D Grid-based Global Positioning System Satellite Signal Shadowing Range Modeling in Urban Area
Highlights
Autonomous driving systems are composed of body control technologies that reflect the decisions made by artificial intelligence (AI) based on accurately recognizing the driving environment and situation
We proposed a method to model the global navigation satellite system (GNSS) observation environment based on digital surface model (DSM), a grid-based 3D model constructed through drone mapping
We developed an algorithm that automatically models the range of GNSS satellite signals that may be blocked by surrounding obstacles at a point inside the DSM data, and defined this model as the surface elevation mask (SEM)
Summary
Autonomous driving systems are composed of body control technologies that reflect the decisions made by artificial intelligence (AI) based on accurately recognizing the driving environment and situation. We analyzed the SEM modeling results and GPS satellite signal observations to evaluate the modeling results and analyze the GPS data characteristics in areas with severe reception conditions
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