Deep Reinforcement Learning Control for Radar Detection and Tracking in Congested Spectral Environments.
Charles E. ThorntonMark A. KozyR. Michael BuehrerAnthony F. MartoneKelly D. SherbondyPublished in: IEEE Trans. Cogn. Commun. Netw. (2020)
Keyphrases
- reinforcement learning
- control problems
- robotic systems
- detecting and tracking multiple
- multi target tracking
- robot control
- optimal control
- face detection and tracking
- particle filter
- crowded scenes
- false detections
- target recognition
- adaptive control
- partial occlusion
- target detection
- control system
- human operators
- human detection
- autonomous robots
- false alarms
- millimeter wave
- real time
- detection algorithm
- control strategy
- detection rate
- hyperspectral
- signal processing
- detection method
- person detection
- model free
- action selection
- false positives
- kalman filter
- moving objects
- tracking scheme
- remote sensing
- multi agent
- change detection
- reinforcement learning algorithms
- visual tracking
- high resolution
- function approximation
- particle filtering
- control method