141 citations · 156 across the 15 of their papers we have counts for
6 papers · 1 filter
Online Learning-based Waveform Selection for Improved Vehicle Recognition in Automotive Radar
Charles E. Thornton, William W. Howard, R. Michael Buehrer
This paper describes important considerations and challenges associated with online reinforcement-learning based waveform selection for target identification in frequency modulated…
When is Cognitive Radar Beneficial?
Charles E. Thornton, R. Michael Buehrer
When should an online reinforcement learning-based frequency agile cognitive radar be expected to outperform a rule-based adaptive waveform selection strategy? We seek insight rega…
Timely Target Tracking in Cognitive Radar Networks
William W. Howard, Charles E. Thornton, R. Michael Buehrer
We consider a scenario where a fusion center must decide which updates to receive during each update period in a communication-limited cognitive radar network. When each radar node…
Linear Jamming Bandits: Sample-Efficient Learning for Non-Coherent Digital Jamming
Charles E. Thornton, R. Michael Buehrer
It has been shown (Amuru et al. 2015) that online learning algorithms can be effectively used to select optimal physical layer parameters for jamming against digital modulation sch…
Online Bayesian Meta-Learning for Cognitive Tracking Radar
Charles E. Thornton, R. Michael Buehrer, Anthony F. Martone
A key component of cognitive radar is the ability to generalize, or achieve consistent performance across a range of sensing environments, since aspects of the physical scene may v…
Universal Learning Waveform Selection Strategies for Adaptive Target Tracking
Charles E. Thornton, R. Michael Buehrer, Harpreet S. Dhillon +1
Online selection of optimal waveforms for target tracking with active sensors has long been a problem of interest. Many conventional solutions utilize an estimation-theoretic inter…