10 June 1994 Robust centralized predetection fusion for enhanced target detection
Author Affiliations +
Abstract
The evolutionary design, signal conditioning, performance prediction and validation with experimental data of robust centralized fusion algorithms (CFAs) that operate in clutter, with unspecified distribution, are presented. Two CFAs, called non-coherent integration and T-squared, followed by an adaptive constant false alarm post-processing along with several variants were evaluated. The fusion algorithms were designed to provide various degrees of robustness and inherent CFAR properties to Weibull and Lognormal clutter. Each algorithm's fusion performance, defined via receiver operating characteristics (ROCs), was compared and also compared to the ROCs of the individual sensors (both by Monte Carlo simulation and by the use of measured data with target in clutter). The test results with both target in the clear and target in clutter data are in concert with the theoretically predicted behavior.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ivan Kadar, Bernard S. Abrams, Louis A. Lovas, Mark G. Alford, William P. Berry, Martin E. Liggins, "Robust centralized predetection fusion for enhanced target detection", Proc. SPIE 2232, Signal Processing, Sensor Fusion, and Target Recognition III, (10 June 1994); doi: 10.1117/12.177766; https://doi.org/10.1117/12.177766
PROCEEDINGS
19 PAGES


SHARE
Back to Top