1 citations · 1 across the 12 of their papers we have counts for
14 papers
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…
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…
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…
Timely Target Tracking: Distributed Updating in Cognitive Radar Networks
William W. Howard, Anthony F. Martone, R. Michael Buehrer
Cognitive radar networks (CRNs) are capable of optimizing operating parameters in order to provide actionable information to an operator or secondary system. CRNs have been propose…
Hybrid Cognition for Target Tracking in Cognitive Radar Networks
William W. Howard, R. Michael Buehrer
This work investigates online learning techniques for a cognitive radar network utilizing feedback from a central coordinator. The available spectrum is divided into channels, and…
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…
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…
Model Order Estimation in the Presence of multipath Interference using Residual Convolutional Neural Networks
Jianyuan Yu, William W. Howard, Yue Xu +1
Model order estimation (MOE) is often a pre-requisite for Direction of Arrival (DoA) estimation. Due to limits imposed by array geometry, it is typically not possible to estimate s…
Decentralized Bandits with Feedback for Cognitive Radar Networks
William Howard, R. Michael Buehrer
Completely decentralized Multi-Player Bandit models have demonstrated high localization accuracy at the cost of long convergence times in cognitive radar networks. Rather than mode…
Distributed Online Learning for Coexistence in Cognitive Radar Networks
William Howard, Anthony Martone, R. Michael Buehrer
This work addresses the coexistence problem for radar networks. Specifically, we model a network of cooperative, independent, and non-communicating radar nodes which must share res…
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…
Multi-Target Localization Using Polarization Sensitive Arrays
William W. Howard, R. Michael Buehrer
In this work we develop clustering techniques for the Bearing Only Target Localization (BOTL) problem. Our scenario has a receiver move along some path, generating bearing estimate…
Multi-player Bandits for Distributed Cognitive Radar
William W. Howard, Charles E. Thornton, Anthony F. Martone +1
With new applications for radar networks such as automotive control or indoor localization, the need for spectrum sharing and general interoperability is expected to rise. This pap…
Direction of Arrival Estimation for a Vector Sensor Using Deep Neural Networks
Jianyuan Yu, William W. Howard, Daniel Tait +1
A vector sensor, a type of sensor array with six collocated antennas to measure all electromagnetic field components of incident waves, has been shown to be advantageous in estimat…