2D image reconstruction from blurred and disturbed multi parameter measurements at the example of an inductive metal detector

Metal detectors (MD), based on the eddy current principle, are widely-used in humanitarian demining. The sensor signal (i.e. the induced complex coil voltage) is influenced by the object properties (material, shape). This effect was used in previous research projects to classify suspicious objects. But the identification of multi-target situations (a mine covered by a neighboring metal object) was still unsolved. From a 2D raw data image only shapes larger than the coil diameter can be visualized. In this paper the deconvolution of multivariate spatial referenced MD-data is used for imaging object distributions, shapes and material properties. The key to a high resolution image reconstruction is the reduction of disturbance influences caused by soils with magnetic properties. The ability to identify multi-target situations and recognize mines by their characteristic metal distribution was demonstrated on test lanes for mine detection provided by the University of Rostock and the CTRO-Benkovac.