Extracting spectral features from a signal in a multiplicative and additive noise environment

Abstract

A spectral feature extracting engine, chirp detecting engine, and target classifying engine with corresponding method, system, and computer product are provided. Given a 'noisy' signal having multiplicative and additive noise, the spectral feature extracting engine extracts spectral features from the noisy signal in the form of a spectral detection density. The extraction includes identifying an initial detection by comparing the spectral content of a subject time-frequency slice with an initial detection threshold calculated from a set of time-frequency slices, and determining the spectral detection density as a function of a number of identified initial detections and number of compared time-frequency slices. Based on the spectral detection density of the noisy signal, the chirp detecting engine detects multiple channel-induced and target-induced chirps present in the noisy signal and the target classifying engine classifies a target from the noisy signal.