Antenna array processing for radar applications using support vector machines

@inproceedings{citeulike:2421436, abstract = {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.}, author = {Xu, Nan and Christodoulou, C. G. and Martinez-Ramon, M. and Ozdemir, T. }, booktitle = {Antennas and Propagation Society International Symposium 2006, IEEE}, citeulike-article-id = {2421436}, doi = {10.1109/APS.2006.1710781}, journal = {Antennas and Propagation Society International Symposium 2006, IEEE}, keywords = {antenna, applications, array, processing, radar, svm}, pages = {1295--1298}, posted-at = {2008-02-24 13:27:13}, priority = {2}, title = {Antenna array processing for radar applications using support vector machines}, url = {http://dx.doi.org/10.1109/APS.2006.1710781}, year = {2006} }

TY - CONF ID - citeulike:2421436 L3 - citeulike-article-id:2421436 TI - Antenna array processing for radar applications using support vector machines T2 - Antennas and Propagation Society International Symposium 2006, IEEE JF - Antennas and Propagation Society International Symposium 2006, IEEE SP - 1295 EP - 1298 N2 - 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. KW - antenna KW - applications KW - array KW - processing KW - radar KW - svm AU - Xu, Nan AU - Christodoulou, CG AU - Martinez-Ramon, M AU - Ozdemir, T PY - 2006/// UR - http://dx.doi.org/10.1109/APS.2006.1710781 ER -