The Coastal Systems Station (CSS) at Panama City, FL is developing an airborne multispectral sensor system which flies on an unmanned aerial vehicle for detecting mines in a coastal environment. This system is called the Coastal Battlefield Reconnaissance and Analysis (COBRA) system and has successfully completed preliminary developmental testing (DT-0). For this program, the Environmental Research Institute of Michigan (ERIM) developed a fieldable ground station including integrated aircraft tracking, real-time sensor data analysis, and a post processor testbed for developing and evaluating mine and minefield detection algorithms. A fully adaptive multispectral Constant False Alarm Rate mine detection algorithm was implemented in the post-processor by ERIM, along with patterned and scatterable minefield detection algorithms developed by CSS. The algorithms do not require prior knowledge of mine spectral signatures and thus are ideal for detecting a wide variety of mines with unknown or changing spectral signatures. COBRA DT-0 testing has been performed on actual minefields deployed at coastal and inland test sites. Preliminary results show that the COBRA system, coupled with these algorithms, meets the required minefield detection performance goals. This paper reviews the algorithm theory and implementation, overviews the ground station design, and presents minefield detection results from actual minefield imagery collected over realistic scenes during DT-0 testing.