Utilizing I/Q data to enhance radar detection and accuracy metrics

Abstract

The incorporation of advanced digital processing technologies including high-bandwidth networks, low-cost commercial components, and advanced FPGAs into novel radio frequency (RF) sensors has resulted in significantly increased sensor capabilities while at the same time dramatically increasing the size of the data associated with test events. This work focuses on the development of management tools to analyze these large datasets to increase overall situational awareness and as a result, sensor performance which requires the development of advanced algorithms designed to address data decimation, parallelization of processing, and novel detection and filtering techniques among others. These algorithms are developed and optimized through post-processing existing MIT-LL sensor data in MATLAB.