Vehicle identifications using acoustic sensing

Abstract

Increase in the complexity of battlefield fought in urban areas has brought a high demand for efficient techniques for vehicles detection, classification, identification and tracking in areas of interest. The demand for such efficient techniques is due to complexity of the environment and to sensor limitations. Multi-sensor data fusion can be used for vehicle identification in practical applications such as battlefield surveillance. Multi-sensor data fusion provides significant advantages over single sensor data source. The purpose of this research is to design and implement data fusion software for vehicle surveillance applications using a distributed network of acoustic sensors. The data fusion software will be used in vehicles traffic monitoring in a battlefield and events detection and tracking in secured areas. Implementation and testing results of the developed software are obtained from real data collect from civilian and military vehicles.