The real time estimation of the period of signals that are periodic over short time intervals requires fast algorithms. In this letter, the maximum likelihood (ML) period estimator is derived for a periodic signal with additive white Gaussian noise. A low complexity approximation is then proposed, and compared with the state of the art of the estimation techniques in a practical scenario for the remote estimation of human heart rate using an ultra wide band radar.
ML period estimation with application to vital sign monitoring
CONTE, ERMANNA;TOMASIN, STEFANO
2010
Abstract
The real time estimation of the period of signals that are periodic over short time intervals requires fast algorithms. In this letter, the maximum likelihood (ML) period estimator is derived for a periodic signal with additive white Gaussian noise. A low complexity approximation is then proposed, and compared with the state of the art of the estimation techniques in a practical scenario for the remote estimation of human heart rate using an ultra wide band radar.
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