Radar Cross Section Model Optimisation Using Genetic Algorithms

Many missile–target simulation systems use random numbers to mimic the effects of a fluctuating target Radar Cross Section (RCS) in an attempt to minimise simulation times. In this paper a Genetic Algorithm is used to optimise the complexity of a pointscatterer model with a realistic radar cross section, ultimately allowing real measured data to be used in simulations. The performance of the genetic algorithm is compared against an iterative optimisation method and a known optimum solution. The radar cross section models described in this paper are designed to be used with a synthetic homing guidance missile in 3-dimensional virtual engagement scenarios. The models allow measured RCS data to be combined with synthetic RCS details, creating a realistic target radar cross section with 4π steradian coverage.