Nonlinear Least Squares Estimation for Breathing Monitoring Using FMCW Radars

In this paper we propose a novel framework for breathing monitoring, based on a simple Nonlinear Least Squares (NLS) estimation, which explores the harmonic structure of the breathing displacement signal. The first part of the study was performed using a controlled target which could be programmed for executing breathing-like movements, thus emulating the chest-wall displacement over time. Finally, the proposed approach was evaluated with real human data, and the results have shown robust and accurate estimation, outperforming previous methods over different scenarios.