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20112024
most citedDeep Reinforcement Learning Control for Radar Detection and Tracking in Congested Spectral Environments

141 citations · 170 across the 18 of their papers we have counts for

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12 papers · 1 filter

eess.SP2022

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…

eess.SP2022

Weight Selection for Pattern Control of Paraboloidal Reflector Antennas with Reconfigurable Rim Scattering

R. Michael Buehrer, Steve W. Ellingson

It has been recently demonstrated that modifying the rim scattering of a paraboloidal reflector antenna through the use of reconfigurable elements along the rim facilitates sidelob…

eess.SP2021

Differential Deep Detection in Massive MIMO With One-Bit ADC

Don-Roberts Emenonye, Carl Dietrich, R. Michael Buehrer

This article presents a differential detection scheme for the uplink of a massive MIMO system that employs one-bit quantizers on each receive antenna. We focus on the detection of…

eess.SP2021

Adversarial Multi-Player Bandits for Cognitive Radar Networks

William W. Howard, R. M. Buehrer, Anthony Martone

We model a radar network as an adversarial bandit problem, where the environment pre-selects reward sequences for each of several actions available to the network. This excludes en…

eess.SP20214 cited

Classification of Common Waveforms Including a Watchdog for Unknown Signals

C. Tanner Fredieu, Justin Bui, Anthony Martone +3

In this paper, we examine the use of a deep multi-layer perceptron model architecture to classify received signal samples as coming from one of four common waveforms, Single Carrie…

eess.SP2021

Open Set Wireless Standard Classification Using Convolutional Neural Networks

Samuel R. Shebert, Anthony F. Martone, R. Michael Buehrer

In congested electromagnetic environments, cognitive radios require knowledge about other emitters in order to optimize their dynamic spectrum access strategy. Deep learning classi…