Wireless Biometric Individual Identification Utilizing Millimeter Waves

Abstract

Biometrics offer a personal and convenient way of keeping our identities and our data secure. Here, we introduce a method of using mm-wave sensors to identify various individuals. In our system prototype, the compact radar sensor has two transmit antennas and four receive ones. The transmitter(s) send a sequence of signals which are reflected and scattered from a nearby part of the body of a user (a hand in our demo case). Different signal processing algorithms are applied to the received signals in order to create a rich feature dataset. In our demo system, the resulting dataset is classified using a random forest machine learning model, which is shown to facilitate identifying a group of individuals with high accuracy. This technology has promising implications in terms of using mm-wave radars as an independent or an auxiliary tool for biometric authentication.