Abstract

Spectrally correlated processes are harmonizable processes characterized by spectral measures concentrated within a countable union of curves. Our study focuses on the spectral analysis of spectrally correlated processes, particularly in scenarios where these support curves take the form of lines with possible non-unit slopes. This class of spectrally correlated processes finds practical application in, for example, the problem of locating moving sources like aircraft, rockets, or other hostile jamming emitters emitting communication signals. We propose a frequency-smoothed periodogram along the support line as the spectral density function estimator. We prove its mean-square consistency and derive its asymptotic distribution. Based on these results, we discuss the asymptotic properties of the introduced coherence estimator. Additionally, we formulate a subsampling technique tailored for spectral analysis of spectrally correlated processes.