An Improved ESPRIT Algorithm for Fast Frequency Estimation

摘要

An improved fast ESPRIT frequency estimation algorithm is present for reducing the computational load existing in frequency estimation of subspace rotational in variance technology (ESPRIT) algorithm. The improved algorithm does not need eigen-decomposition of auto-covariance matrix, using the sampling signal delay data to construct two sub-arrays with the same array shape, through generalized eigen-decomposition of the matrix pencil constructed by the two sub-arrays cross-covariance matrix, to achieve a fast frequency estimation of signal. The simulation results show that the frequency estimated performance of the improved ESPRIT algorithm is comparable to the standard ESPRIT algorithm, and its computational load can be reduced to the fifteen percent of the standard ESPRIT algorithm, so can be used in real time processing system.