A new RCS statistical model of radar targets

In this paper, we point out the drawbacks of conventional target fluctuation models used in radar target modeling. It is usually difficult for us to statistically model a real target by a conventional target model which has an analytical probability density function (pdf) expression, because there are very few parameters which can be used to approximate in conventional target models the pdf of the radar cross section (RCS) of a real target. We suggest a new method of statistical modeling, where the first nth central moment of the RCS data for real targets, combining with the Legendre orthogonal polynomials, are used to reconstruct the pdf of the RCS of the target. The relationship between the 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 coefficients. By comparing the errors-of-fit caused by both the new model and the conventional models, we conclude that the new nonparametric method for statistical modeling of radar targets is superior, for it makes the statistical modeling of radar target easier and more exact.