Abstract
This paper describes a procedure for generating conservative radar cross section (RCS) models able to meet the computational requirements imposed by simulation and related applications. The key concept is to downsample calculated or measured RCS data retaining local extreme values; thus, a conservative RCS matrix is obtained. Spline approximations are used in order to obtain continuity in the RCS models. RCS models with varying resolution have been generated and analyzed, and it is shown how spatial Fourier transforms can be used when determining feasibility for certain decision making applications. Furthermore, it is found that the interpolation errors obtained from the conservative RCS models are well described by generalized extreme value theory.
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