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20112026
most citedDeep Reinforcement Learning Control for Radar Detection and Tracking in Congested Spectral Environments

141 citations · 290 across the 58 of their papers we have counts for

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Showing 2023 · eess.SPShow all

7 papers · 2 filters

eess.SP2023

Mode Selection in Cognitive Radar Networks

William W. Howard, Samuel R. Shebert, Anthony F. Martone +1

Cognitive Radar Networks, which were popularized by Simon Haykin in 2006, have been proposed to address limitations with legacy radar installations. These limitations include large…

eess.SP2023

Mode Selection and Target Classification in Cognitive Radar Networks

William W. Howard, Samuel R. Shebert, Benjamin H. Kirk +1

Cognitive Radar Networks were proposed by Simon Haykin in 2006 to address problems with large legacy radar implementations - primarily, single-point vulnerabilities and lack of ada…

eess.SP2023

Open and Closed-Loop Weight Selection for Pattern Control of Paraboloidal Reflector Antennas with Reconfigurable Rim Scattering

R. Michael Buehrer, William W. Howard, Steven Ellingson

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

eess.SP2023

RIS-Aided Kinematic Analysis for Remote Rehabilitation

Don-Roberts Emenonye, Anik Sarker, Alan T. Asbeck +2

This paper is the first to introduce the idea of using reconfigurable intelligent surfaces (RISs) as passive devices that measure the position and orientation of certain human body…

eess.SP2023

On the Value of Online Learning for Radar Waveform Selection

Charles E. Thornton, R. Michael Buehrer

This paper attempts to characterize the kinds of physical scenarios in which an online learning-based cognitive radar is expected to reliably outperform a fixed rule-based waveform…

eess.SP2023★ 6 cited

Line-of-Sight Probability for Outdoor-to-Indoor UAV-Assisted Emergency Networks

Gaurav Duggal, R. Michael Buehrer, Nishith Tripathi +1

For emergency response scenarios like firefighting in urban environments, there is a need to both localize emergency responders inside the building and also support a high bandwidt…

eess.SP2023

Open Set Wireless Signal Classification: Augmenting Deep Learning with Expert Feature Classifiers

Samuel R. Shebert, Benjamin H. Kirk, R. Michael Buehrer

In shared spectrum with multiple radio access technologies, wireless standard classification is vital for applications such as dynamic spectrum access (DSA) and wideband spectrum m…