no code implementations • 30 Nov 2023 • William W. Howard, Samuel R. Shebert, Anthony F. Martone, R. Michael Buehrer
Cognitive Radar Networks, which were popularized by Simon Haykin in 2006, have been proposed to address limitations with legacy radar installations.
no code implementations • 25 Oct 2023 • William W. Howard, Samuel R. Shebert, Benjamin H. Kirk, R. Michael Buehrer
The goal of the network is to learn over many target tracks both the characteristics of the targets as well as the optimal action choices for each type of target.
no code implementations • 7 Feb 2023 • Samuel R. Shebert, Benjamin H. Kirk, R. Michael Buehrer
To address unknown signals, we propose an open set hybrid classifier, which combines deep learning and expert feature classifiers to leverage the reliability and explainability of expert feature classifiers and the lower computational complexity of deep learning classifiers.
no code implementations • 3 Aug 2021 • Samuel R. Shebert, Anthony F. Martone, R. Michael Buehrer
The closed set classifier achieves an average accuracy of 94. 5% for known signals with SNR's greater than 0 dB, but by design, has a 0% accuracy detecting signals from unknown classes.