Abstract: This paper describes an automatic mine detection algorithm (AMDA) based on the template matching technique. Specifically, this paper demonstrates that regardless of sensor artifacts and other perplexities including environment effects such as terrain variation or weather conditions, there will be distinctive information between targets and clutter imbedded in the signatures for the discrimination. This paper also includes the data analysis of the ground penetration radar signatures and quantifies the AMDA performance. This paper use a subset of the DARPA clutter data collected with the Geo-Centers ground penetration radar at Fort A.P. Hill and Fort Carson. This subset contains anti-personnel, and anti-tank mines buried from 1 to 6 inches deep with the size of the mine ranging from 2 to 12 inches in diameter. The total number of mines and the area coverage of this subset are about 30 and 600m$+2$/, respectively. !3
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