Networks of simple sensors for detecting emplacement of improvised explosive devices

Abstract

Detection of improvised explosive devices is difficult and requires a wide spectrum of strategies. Detection during emplacement is the best hope. Nonimaging sensors provide several advantages over cameras in expense, robustness, and processing simplicity for this task. We describe experiments with inexpensive commercial sensors, and show how data can be combined to provide monitoring for suspicious pedestrian behavior at a 1-10 meter scale. Our approach preanalyzes terrain to rate likelihood of emplacement. We install sensors and monitor the terrain, seeking direct clues to suspicious behavior such as loitering and odd sounds such as excavation. We also use sensor data to track people by inferring their probability distributions, and use this to detect significant accelerations and atypical velocity vectors, both of which can indicate suspicious behavior. We describe experiments we have conducted with a prototype sensor network of eight kinds of sensors, from which it appears that motion and sonar sensors are the most helpful for this task.