Radar has evolved from a complex, high-end aerospace technology into a relatively simple, low end solution penetrating industrial, automotive and consumer market segments. This rapid evolution has been driven by two main factors: advancements in silicon and packaging technology that has led to miniaturization, and growth of computing power that has enabled the use of deep learning algorithms to tap the full potential of radar signals. Radar sensing has enabled several interactive human-machine interface applications and its application continues to grow multi-fold in recent years. For adoption of short-range radars for several industrial, consumer and in-cabin automotive applications require reliable system performance at small form factor, low-power and low-cost.
To enable interactive radar sensing applications advanced signal processing and deep learning algorithms are required that can parse the radar return echo into meaningful target information or understanding the user’s intent. In this talk, we demonstrate and highlight how radar processing are enabling two interactive applications, namely gesture sensing and human localization & tracking, which finds use in several advanced industrial, consumer and in-cabin applications.