This paper describes a robust approach to acquisition of unresolved infrared (IR) targets in clutter. This approach is based on an optimized combination of post-detection and predetection processes. The algorithm utilizes a priori knowledge of target size and velocity relative to the background to suppress background clutter and enhance target signature. The predetection algorithm is based on a maximum likelihood ratio detection model where no statistical assumptions are made on the background. Background clutter is suppressed by background estimation and removal. The target signature is enhanced by applying a space-time filter matched to the target size and velocity after the background has been estimated and removed. The post-detection process further enhances Pd and suppresses Pfa by using an M out of N detection criteria. A performance figure, signal-to-noise ratio improvement factor (SIF) is defined. Sensitivities to SIF from the background estimation and removal process are derived and shown for an image edge primitive. Image edge magnitudes are measured in a MWIR image sequence and used to predict SIF, and the predicted SIF is compared to theoretical results.

Date Published: 1 August 1991
PDF: 11 pages
Proc. SPIE 1481, Signal and Data Processing of Small Targets 1991, (1 August 1991);

Published in SPIE Proceedings Vol. 1481:
Signal and Data Processing of Small Targets 1991
Oliver E. Drummond, Editor(s)