Chang, Chein-IRen, HsuanChiang, Shao-Shan2024-06-112024-06-112001-04Chang, Chein-I., Hsuan Ren, and Shao-Shan Chiang. “Real-Time Processing Algorithms for Target Detection and Classification in Hyperspectral Imagery.” IEEE Transactions on Geoscience and Remote Sensing 39, no. 4 (April 2001): 760–68. https://doi.org/10.1109/36.917889.https://doi.org/10.1109/36.917889http://hdl.handle.net/11603/34571The authors present a linearly constrained minimum variance (TCMV) beamforming approach to real time processing algorithms for target detection and classification in hyperspectral imagery. The only required knowledge for these LCMV-based algorithms is targets of interest. The idea is to design a finite impulse response (FIR) filter to pass through these targets using a set of linear constraints while also minimizing the variance resulting from unknown signal sources. Two particular LCMV-based target detectors, the constrained energy minimization (CEM) and the target-constrained interference-minimization filter (TCIMF), are presented. In order to expand the ability of the LCMV-based target detectors to classification, the LCMV approach is further generalized so that the targets can be detected and classified simultaneously. By taking advantage of the LCMV-based filter structure, the LCMV-based target detectors and classifiers can be implemented by a QR-decomposition and be processed line-by-line in real time. The experiments using HYDICE and AVIRIS data are conducted to demonstrate their real time implementation.9 pagesen-USThis work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.Public Domainhttps://creativecommons.org/publicdomain/mark/1.0/Array signal processingDetectorsFinite impulse response filterHyperspectral imagingHyperspectral sensorsImage processingInterference constraintsObject detectionRemote monitoringSensor arraysText