Accession Number : ADA327076
Title : Performance of Power-Law Processor with Normalization for Random Signals of Unknown Structure.
Descriptive Note : Progress rept.,
Corporate Author : NAVAL UNDERSEA WARFARE CENTER NEWPORT DIV RI
Personal Author(s) : Nuttall, Albert H.
PDF Url : ADA327076
Report Date : 05 MAY 1997
Pagination or Media Count : 95
Abstract : A signal (if present) is located somewhere in a band of frequencies characterized by a total of N search bins, along with uniform noise of unknown level per bin, N. The signal occupies an arbitrary set of N of these bins, where not only is the extent N unknown, but, in addition, the locations of the particular N bins occupied by the signal (if present) are unknown. Also, the average signal level in an occupied bin, S, is arbitrary and unknown. In order to realize a specified false alarm probability, the power-law processor has been normalized by division with an estimate of the noise level, either from a noise only reference or from the measured data itself. Various combinations of normalizer forms have been investigated quantitatively through their receiver operating characteristics. It has been found that if the number of bins, M, occupied by the signal is small relative to the search size N, the additional signal-to-noise ratio required by the normalizer, in order to maintain the standard operating point, is not significant. However, if M is of the order of N/4 or larger, the degradations begin to become substantial. A partial remedy for the inherent losses caused by an unknown noise level is the use of a noise-only data reference, if available. However, eventually, as M increases and tends to N, the detection situation becomes progressively more difficult, finally becoming impossible. This is not a limit of the normalized power-law processor, but, rather, of the fact that detection of a white signal in white noise of unknown level is a theoretical impossibility.
Descriptors : *WHITE NOISE, *PROBABILITY DENSITY FUNCTIONS, DETECTION, SIGNAL TO NOISE RATIO, FALSE ALARMS, FREQUENCY BANDS, SEARCHING, BACKGROUND NOISE.
Subject Categories : Statistics and Probability
Acoustic Detection and Detectors
Magnetic & Electric Fld Detection & Detectors
Distribution Statement : APPROVED FOR PUBLIC RELEASE