High resolution spectral estimation

AR (autoregressive) modelling of a given time series usually yields high-resolution spectral estimates when the observed process is free from noise. Presence of noise however results in biased frequency estimates. In this paper, an adaptive bias elimination technique (ABET) is proposed which first estimates adaptively the noise power and uses it in a new algorithm which reduces the bias, resulting in improved spectral estimation. ABET is particularly suited for tracking the frequencies of sinusoids in a stationary white noise.