Target detection in sensor network using a Zamboni and scan statistics

Abstract

In this article we introduce a sequential procedure for detecting a target using distributed sensors in a two dimensional region. The detection is carried out in a mobile fusion center (in a way familiar to hockey fans, we envision this as a Zamboni machine) which successively counts the number of binary decisions reported by local sensors lying inside its field of view. The proposed sequential detection procedure is based on a two-dimensional scan statistic - this is an emerging tool from the statistics field that has been applied to a variety of anomaly detection problems such as of epidemics or computer intrusion; but that seem to be unfamiliar within the signal processing community. Analytical and simulation results are presented for system-level detection.