Location

https://ccse.kennesaw.edu/computing-showcase/cday-programs/fall23program.php

Streaming Media

Event Website

https://anthonydesantiago.github.io/Spectrum_Analyzer_Tool/

Document Type

Event

Start Date

30-11-2023 4:00 PM

Description

Military test ranges utilize a variety of Radio Frequency (RF) threat systems, to assess the effectiveness of Electronic Warfare (EW) systems during flight tests. A component of this process involves monitoring RF transmissions. Traditionally, system engineers at Robins Airforce Base have manually analyzed video from spectrum analyzers to confirm properties of specific threat systems. To streamline this analysis, our team's aim was to develop an automated solution for RF spectrum analysis. We employed a custom YOLO V8 model to isolate the analyzer screen and used a novel combination of frame differencing, summing, and agglomerative clustering techniques to extract relevant properties of measured signals. Our resulting application significantly reduces human interaction, enhances accuracy, and allows for the transformation of video data into a digitally manipulatable numeric format.

Share

COinS
 
Nov 30th, 4:00 PM

UR-409 Enhancing Aircraft Electronic Warfare Testing with Automated RF Spectrum Analysis

https://ccse.kennesaw.edu/computing-showcase/cday-programs/fall23program.php

Military test ranges utilize a variety of Radio Frequency (RF) threat systems, to assess the effectiveness of Electronic Warfare (EW) systems during flight tests. A component of this process involves monitoring RF transmissions. Traditionally, system engineers at Robins Airforce Base have manually analyzed video from spectrum analyzers to confirm properties of specific threat systems. To streamline this analysis, our team's aim was to develop an automated solution for RF spectrum analysis. We employed a custom YOLO V8 model to isolate the analyzer screen and used a novel combination of frame differencing, summing, and agglomerative clustering techniques to extract relevant properties of measured signals. Our resulting application significantly reduces human interaction, enhances accuracy, and allows for the transformation of video data into a digitally manipulatable numeric format.

https://digitalcommons.kennesaw.edu/cday/2023fall/Undergraduate_Research/2