Multiple target detection and track identification using modified high order correlations

Abstract

This paper is concerned with multiple dim target detection under heavily cluttered background from infrared (IR) satellite data. A new scheme which referred to as order correlation was recently developed which recursively computes the spatio-temporal cross-correlations between data of consecutive scans. In this paper, a new method is developed to identify each individual track in the scene by using the properties of the high order correlation method. A scoring process is also used to improve the discrimination ability of the scheme by employing velocity and curvature information. This new method not only significantly improves the clutter rejection rate, but also increases the feasibility of the modified high order correlation method for other areas such as track identification, data association, classification and tracking. Simulation results are also presented. >