Processing Techniques For Improving Target Identification In Uxo Investigations With Noisy Tdem Data

High noise levels due to terrain, culture, and geologic sources are often unavoidable in UXO investigations. Higher noise levels increase costs due to increased 'no find' responses, and reduce<br>confidence that sources have not been obscured. To improve target identification in noisy TDEM data sets, several processing techniques were compared using evaluation plots with known sources or intrusively investigated data sets. A model for separating noise it into a component that correlates between individual time gate responses, and one that does not, is discussed. Techniques examined for identifying and reducing noise include power-law decay model misfit, time gate sums, and a noise suppression filter based on decay profiles. All of these approaches show potential benefits for reviewing data sets and improving target selection.