Long-range accurate ranging of millimeter-wave retro-reflective tags in high mobility

In this paper, we demonstrate Adaptive Millimetro as an extension of Millimetro, an ultra-low power millimeter-wave (mmWave) retro-reflector presented in [1], for high mobility scenarios. Adaptive Millimetro makes use of automotive radars and enables communication with and accurate localization of roadside infrastructure overextended distances (i.e. >100m). Millimetro achieves this by designing ultra-low-power retro-reflective tags that operate in the mmWave frequency band and can be embedded in road signs, pavements, bi-cycles, or even the clothing of pedestrians. Millimetro addresses the severe path loss problem of mmWave signals by combining coding gain and retro-reflective antenna front-end to achieve long-range operation. However, highly mobile scenarios may still experience unreliable performance due to the Doppler effect changing the received signals. In this paper, we demonstrate a simple solution for robust localization in high mobility by implementing a Moving Target Indication (MTI) filter and an adaptive Kalman filter. We also present an augmented reality app, as an in-car AR platform, that uses Adaptive Millimetro’s algorithms to estimate the tag positions and overlay a virtual box at the estimated locations.