Over the past few years, the Naval Research Laboratory (NRL) has been developing gunfire detection systems using infrared sensors. During the past year, the primary focus of this effort has been on algorithm performance improvements for gunfire detection from infrared imagery. A database of recordings of small arms fire and background clutter is being developed to allow lab testing of new algorithms. As the amount of data continues to grow, the testing analysis becomes lengthier. New tools and methods are being developed to reduce the post analysis time. Results of algorithm improvements for probability of detection and false alarm reduction through use of the database and tools will be presented.
['William Seisler', 'Neil Terry', 'Elmer F. Williams']
Rapid Development of a Gunfire Detection Algorithm Using an Imagery Database