Predicción lineal de norma mínima en la detección de fuentes en ruido

Abstract

This work deals with the problem of detecting deterministic sinusoids in white noise. The procedure, due to kumaresan and Tufts (T-K), is briefly described as a minimum norm exact-linear-prediction design. This method has proved a better performance than currently reported methods in the same field, mainly for very short data records or small number of sensors for angle of arrival estimation in sonar o radar arrays. The algorithm is tested against maximum entropy and phased arrays in order to stablish its performance as concerns with statistical stability, tracking and ROC characteristics.