Denoised Maximum Likelihood Estimation of Chest Wall Displacement from the IR-UWB Spectrum

We present a novel method of estimating the chest wall displacement in the frequency domain from a narrow portion of the IR-UWB radar received spectrum. A Maximum Likelihood (ML) estimator of the displacement is designed, and the associated bias and Cramér-Rao lower bound of the ML estimator are analyzed. To improve estimation accuracy, empirical mode decomposition is applied to denoise the ML-estimated displacement. Simulation studies are conducted to evaluate the performance of the proposed method under realistic system parameter values. The computational complexity of the proposed method is low and equal to that of the Discrete Fourier Transform.