ABSTRACT
The ever-increasing demand in surveillance is to produce highly accurate target identification and estimation in real time, even for dense target scenarios and in regions of high track contention. Past surveillance sensor systems have relied on individual sensors to solve this problem; however, current and future needs far exceed single sensor capabilities. The use of multiple sensors, through more varied information, has the potential to greatly improve state estimation and track identification. Fusion of information from multiple sensors is part of a much broader subject called data or information fusion, which for surveillance applications is defined as “a multilevel, multifaceted process dealing with the detection, association, correlation, estimation, and combination of data and information from multiple sources to achieve refined state and identity estimation, and complete and timely assessments of situation and threat”.
