Towards Modeling GPS Noise via Raytracing

Abstract: Autonomous robot navigation relies heavily on visual-inertial state estimation, which inherently accumulates drift over extended trajectories. Fusing Global Navigation Satellite System (GNSS) signals mitigates this drift, but evaluating these systems in hardware is resource-intensive. Therefore, existing works often rely on simplified, static noise models to generate GNSS measurements. This thesis presents a raytracing-based GPS simulator integrated with Unity using the Flightmare framework to model realistic signal degradation in complex environments. By computing downward ray intersections from real satellite orbital positions, the simulator dynamically measures signal attenuation through foliage--using Weissberger's Modified Exponential Decay model--and building obstructions. Instead of relying on geometric position dilution of precision (DOP), the system constructs a measurement noise covariance matrix based on Carrier-to-Noise density ratio loss to yield a Weighted Dilution of Precision (WDOP). Experimental validation in simulated canopy and concrete structure environments, along with hardware comparisons against a u-blox GNSS receiver on the Carnegie Mellon University campus, demonstrates that WDOP closely mirrors real-world positioning uncertainty where standard geometric DOP models fail. This work offers a high-fidelity simulation tool for advancing autonomous navigation and sensor fusion in signal-degraded environments. Thesis Committee: Wennie Tabib (chair) Wenshan Wang Jiaoyang Li Albert Xu