Unbiased frequency estimation of narrowband signals using Procrustes type subspace rotation

We consider an improved least square algorithm based on subspace rotations using Procrustes approximation. Robust estimation of the poles of a narrowband signal is achieved by reducing the bias of the estimates. The key idea is to consider the signal as a vector in multi-dimensional space, and to separate the “pure signal” and the noise into two mutually orthogonal components lying in different subspaces. Though the quality of the estimated signal is not much improved as compared to the conventional least square based subspace approaches, the advantage of using the proposed algorithm is the asymptotically unbiased nature of the estimates.