Journal of Algorithms & Computational Technology (Dec 2017)
Research on choices of spectral bins in energy-based frequency estimators under intensive noise
Abstract
This paper presented the problem of wrong choice of spectral bins in the energy-based frequency estimation method under intensive noise, and studied its impact on the frequency estimation. Based on the theory of energy-based method, the causes for wrong location of spectral bins in the traditional estimation method were analyzed. In order to reduce wrong choice rate of spectral bins, two optimizational location strategies of spectral bins were introduced, and the effects of them were confirmed by computer simulation. A numerical test under intensive noise was carried out, in which estimation errors returned by optimizational spectral location strategies were compared. It was demonstrated that the estimation accuracy under intensive noise can be remarkably improved by using optimizational spectral location strategies. In particular, Macleod’s optimizational strategy is strongly suggested because of its prominent advantage in reducing occurrences of wrong location as well as its best performance in frequency estimation.