US Patent 10514770 Hidden Markov model-based gesture recognition with FMCW radar

A gesture recognition system is shown using a 77 GHz FMCW radar system. The signature of a gesturing hand is measured to construct an energy distribution in velocity space over time. A gesturing hand is fundamentally a dynamical system with unobservable “state” (i.e. the type of the gesture) which determines the sequence of associated observable velocity-energy distributions, therefore a Hidden Markov Model is used to for gesture recognition. A method for reducing the length of the feature vectors by a factor of 12 is also shown, by re-parameterizing the feature vectors in terms of a sum of Gaussians without decreasing the recognition performance.