Optimal MmWave Sensor Selection for Bearing-Only Localization in Smart Environments

Nowdays, millimeter wave (mmWave) direction sensors are being used increasingly as general-purpose radars, since they can provide high-level of accuracy for a variety of situations at low-cost. Via mutliple mmWave sensors, bearing estimation can be derived to track the position of a target, while in smart environments several sensors can be deployed. In this work, we provide an optimal sensor selection technique, for choosing which sensors to activate for bearing estimation and which not. The proposed approach is decomposed into training phase, where sensor selection is performed, and operational phase, where bearing estimation is obtained. Via simulation results we evaluate the proposed approach compared with the conventional methodology of utilizing all available data streams.