Common pole estimation in multi-channel exponential data modeling

In this paper we develop a technique for detecting and retrieving the common harmonics in a multi-channel setup. The different (complex) signals are arranged in a set of Hankel matrices. First, we compute the singular value decomposition (SVD) of these matrices in order to denoise and normalize the relevant subspaces. Then a second SVD is applied to detect and select the common subspace. The poles of the harmonics are computed from the common subspace using the total least squares (TLS) technique. This method is very flexible, robust and outperforms existing subspace-based methods. Moreover, it can be applied to an arbitrary number of channels.