An innovative real-time technique for buried object detection

In this letter, a new online inverse scattering methodology is proposed. The original problem is recast into a regression estimation one and successively solved by means of a support vector machine (SVM). Although the approach can be applied to various inverse scattering applications, it results very suitable to deal with the buried object detection. The application of SVMs to the solution of such kind of problems is firstly illustrated. Then, some examples, concerning the localization of a given object from scattered field data acquired at a number of measurement points, are presented. The effectiveness of the SVM method is evaluated also in comparison with classical neural networks based approaches.