activity
20172022
most citedQuality of service based radar resource management using deep reinforcement learning

21 citations · 26 across the 3 of their papers we have counts for

collaborators

5 papers

eess.SP2022★ 5 cited

Quality of service based radar resource management for interference mitigation

Sebastian Durst, Pascal Marquardt, Stefan Brüggenwirth

An intelligent radar resource management is an essential building block of any modern radar system. The quality of service based resource allocation model (Q-RAM) provides a framew…

eess.SP2020★ 21 cited

Quality of service based radar resource management using deep reinforcement learning

Sebastian Durst, Stefan Brüggenwirth

An intelligent radar resource management is an essential milestone in the development of a cognitive radar system. The quality of service based resource allocation model (Q-RAM) is…

cs.LG2019

Avoiding Jammers: A Reinforcement Learning Approach

Serkan Ak, Stefan Bruggenwirth

This paper investigates the anti-jamming performance of a cognitive radar under a partially observable Markov decision process (POMDP) model. First, we obtain an explicit expressio…

eess.SP2019

A Load Balancing Surveillance Algorithm For Multifunctional Radar Resource Management

Tobias Müller, Pascal Marquardt, Stefan Brüggenwirth

For all multifunctional radar systems the allocation of resources plays an outstanding role. Many radars have low priority on surveillance tasks. In challenging situations this lea…

eess.SY2017

Adaptive channel selection for DOA estimation in MIMO radar

David Mateos-Núñez, María A. González-Huici, Renato Simoni +1

We present adaptive strategies for antenna selection for Direction of Arrival (DoA) estimation of a far-field source using TDM MIMO radar with linear arrays. Our treatment is formu…