RadNet: a testbed for mmwave radar networks.

Human sensing with millimeter waves (mmWaves) is rapidly gaining momentum. In particular, mmWave radars are becoming the technology of choice in applications like contactless vital signs monitoring, people tracking, or activity recognition, when preserving the users privacy is a concern. However, single mmWave radar sensors have limited range (up to 6--8 m) and are affected by occlusions. For this reason, covering medium to large indoor spaces requires the deployment of multiple radar devices, i.e., radar networks. Because of the complexity of reflections produced by people moving in real life environments, the development and validation of algorithms for mmWave radar networks can only be fulfilled through extensive experimental campaigns. In this work, we present RadNet, the first experimental testbed for the easy deployment and testing of radar network algorithms. We describe its architecture and functioning and we show experimental results of a multi-radar people tracking algorithm implemented on the RadNet experimental platform.