Spectral estimation based on structured low rank matrix pencil
This paper proposes a new parameter estimation algorithm for damped sinusoidal signals. Parameter estimation for damped sinusoidal signals with additive white noise is a problem of significant interest in many signal processing applications, like analysis of NMR data and system identification. The new algorithm estimates the signal parameters using a matrix pencil constructed from the measured data. To reduce the noise effect, a rank deficient Hankel approximation of the prediction matrix is used. The performance of the new algorithm is significantly improved by structured low rank approximation of the prediction matrix. Computer simulations show that the noise threshold of the new algorithm is significantly better than the existing algorithms.