Cardiac radar for biometric identification using nearest neighbour of continuous wavelet transform peaks

This work explores the use of cardiac data acquired by a 2.4 GHz radar system as a potential biometric identification tool. Monostatic and bistatic systems are used to record data from human subjects over two visits. Cardiac data is extracted from the radar recordings and an ensemble average is computed using ECG as a time reference. The Continuous Wavelet Transform is then computed to provide time-frequency analysis of the average radar cardiac cycle and a nearest neighbor technique is applied to demonstrate that a cardiac radar system has some promise as a biometric identification technology currently producing Rank-1 accuracy of 19% and Rank-5 accuracy of 42% over 26 subjects.