Self-organizing cooperative sensor network for remote surveillance: current results

Abstract

The capabilities of unattended ground sensors (UGSs) have steadily improved and have been shown to be of value in various military missions. Today's UGS are multi-functional, integrated sensor platforms that can detect and locate a wide variety of ground-based and airborne targets. The rather large size (> 1 cubic foot) and relatively expensive cost of these integrated platforms are two main drawbacks for remote surveillance applications that support rapidly deployable, small unit operations. As an alternative, remote surveillance may be possible with smaller, less costly sensors that work cooperatively together as a network. The objective of this study was to develop algorithms that can optimally organized and adaptively control a network of UGSs in order to achieve a surveillance mission. In the present study, the sensor network, a random distribution of acoustic sensors over a surveillance area, is tasked to detect and track any targets entering into the surveillance area. In addition, the sensor network is required to maximize its tracking accuracy and minimize its power utilization.