In March of 1999, a research team from the University of Mississippi brought its data acquisition system consisting of an acoustic/seismic laser Doppler vibrometer (LDV) mine detection sensor, to Fort A P Hill in Virginia. The purpose was to collect data over a variety of miens and to participate in a blind test. IN the blind test, the mine detection apparatus was brought to several 1-m by 1-m areas included a mix of mines, blank spots., and clutter spots as determined from prior test. The data collected over each of these spots was visualized in real time, an a mine/no mine decision was made. The resultant probability of detection was 95 percent with a false-alarm rate (FAR) of 0.03 m-3. We present a description of the test and a detailed analysis of the data collected by the University of Mississippi in the mine lanes at AP Hill. With knowledge of the baseline, we compute target and clutter statistics, including signal-to-clutter ratios for various categories of mine types and mine depths. We examine detection trends as a function of frequency. Applying image-processing techniques to the data, features such as size and shape are extracted, and the resultant feature-level target and clutter histograms are used to improve performance. The expected performance with a without feature is compared to the demonstrated performance.