The application of machine learning to signal processing for detection and identification of signals of interest and anomalies

Jason Marr; Seana Moriarty; Veronica Lott; Anthony Bausas

doi:10.1117/12.2585387

12 April 2021 The application of machine learning to signal processing for detection and identification of signals of interest and anomalies

Jason Marr, Seana Moriarty, Veronica Lott, Anthony Bausas

Author Affiliations +

Proceedings Volume 11756, Signal Processing, Sensor/Information Fusion, and Target Recognition XXX; 117560K (2021) https://doi.org/10.1117/12.2585387
Event: SPIE Defense + Commercial Sensing, 2021, Online Only

Abstract

A Signal of Interest (SOI) is a signal that has been recorded for further analysis. This is driven by mission requirements for both known and anomaly signals. Identifying anomalies/SOIs is reliant on the system operator’s knowledge which can be prone to human error. The objective of our project is to improve situational awareness by automating the identification of SOIs with Machine Learning/Artificial Intelligence (ML/AI) techniques. In this paper, we describe a prototype developed and integrated into the tactical system that streams live Radio Frequency (RF) into our real-time Graphical User Interface (GUI) and implements an Artificial Neural Network (ANN) algorithm with the ability to predict potential anomalies/SOIs in real-time.

Conference Presentation

Citation Download Citation

Jason Marr, Seana Moriarty, Veronica Lott, and Anthony Bausas "The application of machine learning to signal processing for detection and identification of signals of interest and anomalies", Proc. SPIE 11756, Signal Processing, Sensor/Information Fusion, and Target Recognition XXX, 117560K (12 April 2021); https://doi.org/10.1117/12.2585387

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