Fast communication: A Prony-like method for non-uniform sampling
Signal Processing
Damped sinusoidal signals parameter estimation in frequency domain
Signal Processing
Hi-index | 35.68 |
Most of the existing algorithms for parameter estimation of damped sinusoidal signals are based only on the low-rank approximation of the prediction matrix and ignore the Hankel property of the prediction matrix. We propose a modified Kumaresan-Tufts (MKT) algorithm exploiting both rank-deficient and Hankel properties of the prediction matrix. Computer simulation results demonstrate that compared with the original Kumaresan-Tufts (1982) algorithm and the matrix pencil algorithm, the MKT algorithm has a lower noise threshold and can estimate the parameters of signal with larger damping factors