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AI-Enhanced 3D RF Representation Using Low-Cost mmWave Radar

2018-11-04 · SenSys '18 Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems 2018 11 · Shiwei Fang, Shahriar Nirjon

This paper introduces a system that takes radio frequency (RF) signals from an off-the-shelf, low-cost, 77 GHz mm Wave radar and produces an enhanced 3D RF representation of a scene. Such a system can be used in scenarios where camera and other types of sensors do not work, or their performance is impacted due to bad lighting conditions and occlusions, or an alternate RF sensing system like synthetic aperture radar (SAR) is too large, inconvenient, and costly. The enhanced RF representation can be used in numerous applications such as robot navigation, human-computer interaction, and patient monitoring. We use off-the-shelf parts to capture RF signals and collect our own data set for training and testing of the approach. The novelty of the system lies in its use of AI to generate a fine-grained 3D representation of an RF scene from its sparse RF representation which a mm Wave radar of the same class cannot achieve.

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RF-based Pose EstimationRobot Navigation

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