A smart antenna system for direction of arrival estimation based on a support vector regression

In this paper, the use of a smart antenna system for the estimation of the directions of arrival (DOAs) of multiple waves is considered. An efficient method based on the support vector regression is proposed, in which the mapping among the outputs of the array and the DOAs of unknown plane waves is approximated by means of a family of support vector machines. Several numerical results are provided for the validation of the proposed approach, considering multiple impinging waves both in noiseless and noisy environments.

[1]  Bernhard Schölkopf,et al.  A tutorial on support vector regression , 2004, Stat. Comput..

[2]  A. V.DavidSánchez,et al.  Advanced support vector machines and kernel methods , 2003, Neurocomputing.

[3]  Alexander J. Smola,et al.  Asymptotically optimal choice of varepsilon-loss for support vector machines. , 1998 .

[4]  J.T. Kwok,et al.  Linear Dependency betweenand the Input Noise in -Support Vector Regression , 2001 .

[5]  R. O. Schmidt,et al.  Multiple emitter location and signal Parameter estimation , 1986 .

[6]  David Gesbert,et al.  Smart Antennas for Mobile Communications , 2000 .

[7]  D. Rohde,et al.  Experiments on DOA-estimation and beamforming for 60 GHz smart antennas , 2003, The 57th IEEE Semiannual Vehicular Technology Conference, 2003. VTC 2003-Spring..

[8]  T.K. Sarkar,et al.  Direction of arrival estimation based on temporal and spatial processing using a direct data domain (D/sup 3/) approach , 2004, IEEE Transactions on Antennas and Propagation.

[9]  S. Sathiya Keerthi,et al.  Improvements to Platt's SMO Algorithm for SVM Classifier Design , 2001, Neural Computation.

[10]  Jan-Ming Ho,et al.  Travel time prediction with support vector regression , 2003, Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems.

[11]  Yunqian Ma,et al.  Practical selection of SVM parameters and noise estimation for SVM regression , 2004, Neural Networks.

[12]  V. Vapnik Pattern recognition using generalized portrait method , 1963 .

[13]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[14]  Michael Georgiopoulos,et al.  Performance of radial-basis function networks for direction of arrival estimation with antenna arrays , 1997 .

[15]  Michael Georgiopoulos,et al.  A neural network-based smart antenna for multiple source tracking , 2000 .

[16]  B. Schölkopf,et al.  Asymptotically Optimal Choice of ε-Loss for Support Vector Machines , 1998 .

[17]  Harry Leib,et al.  Multiple antenna systems: their role and impact in future wireless access , 2003, IEEE Commun. Mag..

[18]  Alexander J. Smola,et al.  Support Vector Method for Function Approximation, Regression Estimation and Signal Processing , 1996, NIPS.

[19]  Kapil R. Dandekar,et al.  Experimental study of mutual coupling compensation in smart antenna applications , 2002, IEEE Trans. Wirel. Commun..