Automated Gain Control Through Deep Reinforcement Learning for Downstream Radar Object Detection
Tristan S. W. Stevens,
R. Firat Tigrek,
Eric S. Tammam
et al.
Abstract:Cognitive radars are systems that rely on learning through interactions of the radar with the surrounding environment. To realize this, radar transmit parameters can be adapted such that they facilitate some downstream task. This paper proposes the use of deep reinforcement learning (RL) to learn policies for gain control under the object detection task. The YOLOv3 single-shot object detector is used for the downstream task and will be concurrently used alongside the RL agent. Furthermore, a synthetic dataset … Show more
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