Threshold based algorithms for UXO detection using magnetometry

Iron buried objects induce anomalies in the earth's magnetic field that appear on the surface below items and that can be measured by a magnetometer. In this work, two approaches already used in radar detection are introduced and modified to improve the UXO detection. The measurement noises, the weak value of the earth's magnetic field and the variations due to the soil heterogeneity increase the false alarm probability. In order to reduce this last, we introduce a cell-averaging-based threshold algorithm used in radar detection. It consists of doing a comparison between each measure and a weighted average of the neighbor measures. The proposed algorithm is validated using simulation data and promising results have been obtained.