There have been several examples in which both Synthetic Aperture Radar (SAR) and Hyperspectral Imaging (HSI) systems collected data in support of military operations (SMO). FOPEN (Foliage Penetration) radar has been used to penetrate tree canopies in order to detect objects. On the other hand, spectral differences between targets and backgrounds are used in HSI systems. Both SAR and HSI systems may suffer substantial false alarm and leakage rates due to respective background clutter. It is expected that a combined SAR and HSI system will greatly enhance the detection and identification performance. Based on the features derived from SAR and HSI data, a fusion approach has been established. Data sets of SAR and HSI over a common area from the Dixie data collection (May 1997 from Vicksberg, Mississippi) are used in this paper to demonstrate the fusion approach. The site contained several camouflage nets and vehicles. One of the vehicles was covered under a camouflage net. Target detection will be shown for each data set based on RCS (Radar Cross Section) and spectral features. In particular, a transformation of the spectral measurements into principal components was used to reduce the dimensionality of HSI data as well as to facilitate spectral feature extraction and material identification. SAR and HSI detections were subsequently combined via image coregistration. The fusion results showed that false detections in the SAR image were greatly reduced with background characterization of trees from HSI and target detections were confirmed with detection of camouflage nets and material identification of vehicle paints.

Date of creation, presentation, or exhibit



IEEE Radar Conference (1999) 218-220 "SAR and HSI data fusion for counter CC&D," Proceedings of the 1999 IEEE Radar Conference. Institute of Electrical and Electronics Engineers (IEEE). Held in Waltham, Massachusetts: 20-22 April 1999. ©1999 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. This work was sponsored by the Department of Air Force under Contract F19628-95-C-0002. Opinions, interpretations, conclusions and recommendations are those of the authors and not necessarily endorsed by the United States Air Force. ISBN: 078-03-4977-6Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in February 2014.

Document Type

Conference Proceeding

Department, Program, or Center

Chester F. Carlson Center for Imaging Science (COS)


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