As the number of elements on phased array antennas continues to grow, so does the volume of data that must be processed to extract information from the signals gathered. Researchers at the Georgia Institute of Technology have developed a new approach to intelligently process that data closer to where it is generated - on the antenna subarrays themselves.

Combining technologies including machine learning, field-programmable gate arrays (FPGAs), graphics processing units (GPUs), and a new radio-frequency image processing algorithm, the research has streamlined the modular handling of radar signals to reduce processing time and cost. The improvements – as much as two or three orders of magnitude – could lead to real-time analysis of RF image data from sources ranging from potential enemy targets to speeding automobiles headed toward collisions.