Related references
Note: Only part of the references are listed.
Proceedings Paper
Engineering, Electrical & Electronic
Quality of service based radar resource management for interference mitigation
Sebastian Durst et al.
Summary: Intelligent radar resource management is crucial for modern radar systems. The Q-RAM model provides a quantifiable decision-making framework, but lacks flexibility in the presence of interference. This paper extends the Q-RAM framework with an intelligent interference handling capability, incorporating virtual time resources and alternative task configurations to compute near-optimal solutions. Experimental results demonstrate significant improvement over traditional strategies.
2022 IEEE TOPICAL CONFERENCE ON WIRELESS SENSORS AND SENSOR NETWORKS (WISNET) (2022)
Proceedings Paper
Engineering, Electrical & Electronic
Quality of service based radar resource management using deep reinforcement learning
Sebastian Durst et al.
Summary: The study introduces a solution for intelligent radar resource management using deep reinforcement learning, significantly improving runtime performance and providing new insights for the development of cognitive radar systems.
2021 IEEE RADAR CONFERENCE (RADARCONF21): RADAR ON THE MOVE (2021)