ABSTRACT
In this Paper, high resolution methods, such as Multiple Signal Classification (MUSIC), Root MUSIC and Estimation of Signal Parameter via Rotational Invariance Technique (ESPRIT) are discussed that model the data as the output of a linear system driven by white noise, and then attempt to estimate the parameters of that linear system. The comparison of the amplitude, power (squared amplitude) and frequency estimation error, based on Matlab simulations is carried out in order to analyse the performance of MUSIC, RootMUSIC, ESPRIT methods in estimating amplitude, power (squared amplitude) and frequency estimation of synthetic power signal both in clean and noisy conditions. Simulation results are presented on signal using mean square error (MSE) as the evaluation criterion. The variation of amplitude, power (squared amplitude) and frequency estimation are compared with respect to data sequence length and Signal to noise ratio (SNR) and their influences on MSE that demonstrate the performance of the high resolution methods are provided. Also the influences of different estimation methods on MSE are compared.
