An Innovative Real-Time Technique for Buried Object Detection

In this paper, a new on-line 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 (NNs) based approaches. (c) 2003 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.