Likelihood ratio test using edge information for false alarm mitigation

摘要

Abstract: As the sensitivity of next generation IRST systems is improved and the need for detecting dim targets becomes important, it becomes of paramount importance to mitigate the false alarms which occur due to clutter artifacts so that noise limited performance can be achieved. One of the chief sources of false alarms in current IRST systems operating in cloud and ground clutter are scenes with high edge content. Clutter with acute angles has a large amount of power in the mid-band spatial frequencies and will compete with target energy out of the matched filter. Since the simplistic approach of just blanking edge regions would cause targets to be lost, a more sophisticated procedure needs to be developed. The method of false alarm mitigation (FAM) developed in this study is to construct a likelihood ratio test by modeling the probability density of the local SNR discriminant as a combination of a Gaussian and a Gamma distribution and by modeling the edge discriminant with a central chi density when no edge is present and a noncentral chi density when an edge is present. The output of the likelihood ratio test leads to a decision region in the two-dimensional discriminant space for deciding when a target is present versus when a target is absent.!3