Adptive spectral estimation by the conjugate gradient method

Pisarenko´s harmonic retrieval method provides unbiased spectral estimates of a signal consisting of the sum of n sinusoidal signals in additive white noise. Recently, a few adaptive versions based on Pisarenko´s method have been developed. In this paper we propose an alternative technique for adaptive spectral estimation based on the method of conjugate gradient, which is used for iteratively finding the eigenvector corresponding to the minimum eigenvalue of the covariance matrix. The new method is an exact adaptive version of Pisarenko´s method and converges in finite steps for any initial guesses. Simulations have been performed to compare the new method with the existing ones. It is seen that the new method improves the CPU time by a factor of 40. Also, the technique performs very well for both narrow band and wide band signals.