Urban Objects Classification With an Experimental Acoustic Sensor Network

This paper proposes feature extraction methods for object classification with passive acoustic sensor networks deployed in suburban environments. We analyzed the emitted acoustic signals of three object classes: 1) guns (muzzle blast); 2) vehicles (running piston engine); and 3) pedestrians (several footsteps). Based on the conducted analysis,...

Mission-Driven Resource Management for Reconfigurable Sensing Systems

Modern sensors, such as multifunctional radars, comprise many settings and the number of controllable settings is increasing due to technological advance. Although having many settings allows many capabilities, it simultaneously requires an automatic manager to control them. This paper proposes mission-driven resource management to control...