Quality of service based radar resource management using deep reinforcement learning
This addresses the need for efficient resource management in cognitive radar systems, but it appears incremental as it applies an existing method (deep reinforcement learning) to a specific domain problem.
The paper tackled the problem of real-time radar resource management using the Quality of Service based Resource Allocation Model (Q-RAM), and the result was a solution using deep reinforcement learning that considerably improved runtime performance.
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 a framework allowing for intelligent decision making but classical solutions seem insufficient for real-time application in a modern radar system. In this paper, we present a solution for the Q-RAM radar resource management problem using deep reinforcement learning considerably improving on runtime performance.