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A model-based correlation detection scheme is presented with the aim of detecting and localizing subsurface tunnel infrastructure in an automated fashion. Our goal is to develop a comprehensive detection technology that can be fielded and successfully used by nonexperts, while simultaneously being sufficiently robust as to be effective. Our correlation detection algorithm relies on a library of model signals that are generated using an analytical model of a thin subsurface wire in a homogeneous half-space. The wire is illuminated using an active transmitter source (12, 20, or 200 kHz), and its response is sensed using a man-portable electromagnetic gradiometer (EMG) system. The performance of the detector is assessed using synthetic data and receiver operating characteristic (ROC) analysis as well as experimental data collected during a field test. Preliminary ROC results indicate that at sufficient signal-to-noise ratio, the detector can achieve detection probabilities greater than 0.9 with corresponding false alarm rates of less than one every 1000 m. Results from the field tests revealed that the responses from the EMG can be used to detect and localize (to within 0.5 m in the horizontal) a wire target down to a depth of at least 7 m. We believe the EMG system and correlation detector combine to form a promising technology for detecting tunnel infrastructure that can be used by experts and, more importantly, nonexperts as well.