Countering improvised explosive devices with adaptive sensor networks

摘要

The design and architecture of a system for automatic Improvised Explosive Devices detection to protect sensitive areas with minimal human interaction is presented. The system, called ACE for “Army Counter IED Enhanced”, employs a variety of statistical analysis, pattern recognition and human machine interface in conjunction with adaptive mechanisms. ACE combines four different kinds of inputs: image processing, nonvisual inputs, pattern recognition, and Kalman filters. ACE produces three kinds of outputs: a visualization of the area under surveillance, a highlight of potential threats, and alarms that trigger traffic control devices to contain the threat while security forces proceed to confirm and neutralize the threat. Data fusion of the inputs is conducted with a dynamic system assigning weights to the values provided by each input, adding results into a threat assessment value (TAV), in order to compare it to thresholds for alerts and alarms.