An estimation algorithm for AR models with closely located lightly damped low frequency poles

In this paper we present a pole estimation algorithm which is based on an overdetermined adaptive IIR lter with an additional postprocessing stage to extract the pole locations from the adaptive weights. The adaptive ltering algorithm used, is a pseudo-linear regression algorithm which is solved by a time-recursive QR decomposition. Two pole classi cation schemes are presented to separate the true poles and the super uous poles. The classi cation schemes are based on the occurrence of pole-zero cancelation and on the pole movement in the z-plane. Floating point simulations are presented to demonstrate the performance of the proposed algorithm.