A NEW RCS STATISTICAL-MODEL OF RADAR TARGETS

In this paper we point out the drawbacks of conventional target fluctu ation models used in radar target modeling. It is usually difficult fa r us to statistically model st real target by a conventional target mo del which has an analytical probability density function (pdf) express ion, because there are very few parameters which can be used to approx imate in conventional target models the pdf of the radar cross section (RCS) of a real target. We suggest a new method of statistical modeli ng, where the first nth central moment of the RCS data Ear real target s, combining with the Legendre orthogonal polynomials, are: used to re construct the pdf of the RCS of the target, The relationship between t he coefficients of the Legendre polynomials and the central moments of RCS are deduced mathematically. Through a practical computing example , the error-of-fit is shown as a function of the orders of Legendre co efficients. By comparing the errors-of-fit caused by both the new mode l and the conventional models, we conclude that the new nonparametric method for statistical modeling of radar targets is superior, for it m akes the statistical modeling of radar target easier and more exact.