BRDF Modeling In Microwave Band And Parameters Inversion Of Rough Surface

In this paper, the bidirectional reflectance distribution function (BRDF) ofone-dimensional conducting rough surface and dielectric rough surface are calculatedwith different frequencies and roughness values in the microwave band by using themethod of moments, and the relationship between the bistatic scattering coefficient andthe BRDF of rough surface is expressed. From the theory of the parameters of the roughsurface BRDF, the parameters of BRDF are obtained using the genetic algorithm. BRDFof rough surface is calculated using the obtained parameter values. Further, the fittingvalues and theoretical calculations of BRDF are compared, and the optimization resultsare in agreement with the theoretical calculation results. Finally, a reference for BRDFmodeling of Gauss rough surface in the microwave band is provided by the proposedmethod. Finally, support vector machine (SVM) and neural networks in the parametersinversion of rough surface is introduced. The root mean square height and correlationlength of Gauss rough surface are inversed by the support vector machine and neuralnetwork, respectively. The simulation results and the comparisons of inversing errorshow that, in the case of small number of rough surface sample, the inversion results ofsupport vector machine are better than those of the neural network, while in the case ofsufficient number of rough surface sample, the inversion accuracy of neural networkwill increase and the time of inversion by neural network is much less than that of thesupport vector machine.