We present automated anomaly-picking methods for detecting unexploded ordnance (UXO) from broadband electromagnetic (EM) data. Using data consisting of in-phase and quadrature responses at multiple (typically 10) frequencies, a detector function attempts to detect all metal objects but to suppress false alarms caused by geology, variations in sensor height, and sensor motions in the earth's magnetic field.

Promising detector functions considered here are (1) the sum of all quadrature responses, Qsum, (2) the sum of all differences among the in-phase or quadrature components, Ispread or Qspread, (3) the sum of the Ispread and Qspreads, Tspread, (4) the weighted total apparent conductivity (TAC) from all frequencies, and (5) the apparent magnetic susceptibility (AMS) derived from the lowest frequency of a survey. These detector functions favor metallic objects and are relatively insensitive to geologic variations and motion-induced noise, which are common with a handheld or cart-mounted sensor in rough terrain. We discuss the properties of these detector functions, apply them to field data from two sites, and compare the results with limited ground truths. Based on the theoretic study and test on the real data, the total apparent conductivity is the best detector function for picking and classifying anomalies, which shows more distinct anomalies and quieter background than other detector functions.

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