Detection and tracking of an explosives-carrying human with odor-sensor based multisensor networks

In this study, it is aimed to detect and track an explosives-carrying mobile human moving among other humans. To this aim, a least square estimation (LSE) based sensor and data fusion algorithm is developed to work in combination with a multisensor network consisting of odor, sound, and vibration sensors. The results are evaluated by simulations for various paths traveled by two humans, of which one carries an explosive. The simulation results demonstrate problems related to using odor sensors only and the improved performance in detection and path tracking obtained with the addition of sound sensors. The paper is the first reported study using odor sensors in combination with sound sensors for detection and tracking.