stanford graduate
course project

EE 259 Radar Remote Sensing

winter 2023

In a new graduate course, Radar Remote Sensing, taught by Dr. Howard Zebker and Dr. Dustin Schroeder, we explored the fundamentals of using radar as a remote sensing tool. From system design to signal processing, filtering, and final image processing, we applied the principles we learned to processing raw data.

For my final project, I analyzed the idea of using GNSS reflectometry to image the Earth, and backing out the system requirements needed to successfully image the Earth with GNSS signals.

my work

I simulated a GNSS-R setup assuming the configuration shown in this diagram.

Signal uncertainty increases when considering incoherent scattering compared to ideally coherent scattering. This diagram visualizes the increase in uncertainty.

Simulation results outline the expected power received using coherent vs. incoherent assumptions. As the height of the reference receiver, received power decreases significantly.

This is a depiction of a similar LEO GNSS-R configuration found online. Image credit from https://en.wikipedia.org/wiki/ GNSS_reflectometry.

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