Antenna array processing for radar applications using support vector machines

Support vector machines are a good candidate for the solution of antenna array processing problems such as beamforming and the angle of arrival estimation, because these algorithms provide superior performance in generalization ability and computational complexity. In this work we introduce three new approaches for antenna array beamforming based on support vector machines. The first one is based on the use of the linear support vector regressor. The second algorithm uses a nonlinear multiregressor to find the parameters of a linear beamformer and the third is an implementation of a nonlinear beamformer using a nonlinear support vector machine. Comparisons with conventional beamforming strategies and simulation results are provided to demonstrate the advantages of the support vector machine approach