Estimating radar clutter distributions via neural networks

Author

Bucciarelli, T. ; Monopoli, F. ; Parisi, R. ; Lombardo, P.

Author_Institution

Inf. & Commun. Dept., Univ. of Rome La Sapienza, Italy

fYear

1996

fDate

8-10 Oct 1996

Firstpage

135

Lastpage

138

Abstract

A new approach to the solution of constant false alarm rate (CFAR) problems in complex, unknown environment is proposed. An adaptive system is described in which a neural network properly transforms the input random process which describes the clutter amplitude. The network proposed is a modified neural network (Tchebychev neural network), specifically designed for the problem at hand, whose neurons implement Tchebychev polynomials up to a proper order. Experimental results are presented referring to Weibull and Rayleigh input distributions

Keywords

Weibull distribution; neural net architecture; polynomials; probability; radar clutter; radar computing; radar detection; CFAR problems solution; Rayleigh input distribution; Tchebychev polynomials; Weibull input distribution; adaptive system; clutter amplitude; constant false alarm rate; experimental results; input random process; modified Tchebychev neural network; neural architecture; radar clutter distributions; radar detection; Adaptive systems; Artificial neural networks; Clutter; Envelope detectors; Jamming; Neural networks; Neurons; Radar detection; Random processes; Spaceborne radar;

fLanguage

English

Publisher

ieee

Conference_Titel

Radar, 1996. Proceedings., CIE International Conference of

Conference_Location

Beijing

Print_ISBN

0-7803-2914-7

Type

conf

DOI

10.1109/ICR.1996.573790

Filename

573790