Accession Number : ADA296192
Title : PDF Approximation for Radar Data.
Descriptive Note : Rept. for Mar-Oct 94,
Corporate Author : ROME LAB GRIFFISS AFB NY
Personal Author(s) : Slaski, Lisa K. ; Maher, John E.
PDF Url : ADA296192
Report Date : APR 1995
Pagination or Media Count : 47
Abstract : The subject of this report is a new method for approximating the underlying probability density function of random data, called the Osturk Algorithm, and its application to spatial radar clutter data. This algorithm works extremely well with only 100 independent samples.This is an improvement over classical methods which can only determine statistical consistency with a specified distribution and require thousands of independent samples. The efficiency of this algorithm allows the approximation of the probability density function of the spatial clutter data from a much smaller region. This makes it possible to observe changes in clutter statistics over a scan volume. The analysis in this report used the algorithm to approximate how close the data from a clutter measurement experiment was to being Gaussian. This analysis determined that the majority of this spatial clutter data was non-Gaussian. (AN)
Descriptors : *ALGORITHMS, *PROBABILITY DENSITY FUNCTIONS, *RADAR CLUTTER, SIGNAL PROCESSING, SPATIAL DISTRIBUTION, WEIBULL DENSITY FUNCTIONS, STATISTICAL DATA, APPROXIMATION(MATHEMATICS), SAMPLING, RADAR SIGNALS, RANGE(DISTANCE), AZIMUTH, RADAR CORRELATION, RADAR SCANNING, GOODNESS OF FIT TESTS, NORMAL DENSITY FUNCTIONS.
Subject Categories : Statistics and Probability
Active & Passive Radar Detection & Equipment
Distribution Statement : APPROVED FOR PUBLIC RELEASE