Pade approximations to matched-filter amplitude probability functions: Rayleigh mixtures and multiple observations

Volume

38

Issue

2

fYear

2002

fDate

4/1/2002 12:00:00 AM

Firstpage

621

Lastpage

632

Abstract

Techniques are presented for deriving approximations to the statistical functions that characterize linear sums of matched-filter outputs. They are derived using two techniques: (1) Pade approximations to the multidimensional characteristic function (CF), and (2) discrete Rayleigh mixtures based on an exact or approximate form of the Rayleigh parameter probability density function. The Pade-based approximations are used for modeling the "clutter-only" case and computing detection thresholds, whereas the Rayleigh mixtures are best suited for modeling the "target-plus-clutter" case and computing target detection probabilities

Keywords

Bessel functions; Hankel transforms; filtering theory; matched filters; probability; radar clutter; radar detection; radar signal processing; Bessel function; Hankel transform pair; Pade approximations; Rayleigh mixtures; Rayleigh parameter probability density function; clutter-only case; detection thresholds; echolocation systems; fluctuation model; line-of-sight target; linear sums; matched-filter amplitude probability functions; matched-filter outputs; multidimensional characteristic function; multiple observations; multivariate statistical functions; radar clutter; range resolution; receiver operating characteristic curves; search mode; signal-to-clutter ratio; single-observation detection problem; statistical functions; target detection probabilities; target-plus-clutter case; Computer vision; Delay effects; Impedance matching; Matched filters; Multidimensional systems; Object detection; Probability density function; Random variables; Signal processing; Statistics;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/TAES.2002.1008991

Filename

1008991