Vital parameter estimator using LMS and MUSIC for biomedical FMCW radar

Abstract

This paper proposes a vital parameter estimator using LMS (least mean square) and MUSIC (Multiple Signal Classification) for vital FMCW (Frequency Modulated Continuous Wave) radar. In order to estimate the vital parameter for human, vital FMCW radar with high accuracy Doppler frequency is used recently. However, plenty of problems for vital FMCW radar is needed to solve to achieve high accuracy results. In particular, due to low signal-to-noise ratio (SNR) of the heartbeat received signal, vital radar obtains low performance results. In case of low SNR, the super-resolution algorithm such as MUSIC cannot be adapted to vital radar to enhance the resolution parameters. Therefore, in this paper, the proposed method based on an adaptive LMS filter and the MUSIC scheme is analyzed to obtain the Doppler spectral estimation in a low SNR environment. From experimental results, when the distance of two targets is 2m, the proposed method has accurate results in case of the position in low SNR condition.