NDLI: A real-time implementation of the method of principal components applied to dual-polarized radar returns

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Proceedings of the Seventh Workshop on Multidimensional Signal Processing

Sixth Multidimensional Signal Processing Workshop,

Sixth Multidimensional Signal Processing Workshop (Cat. No.89TH0290-7)

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A real-time implementation of the method of principal components applied to dual-polarized radar returns

Content Provider	IEEE Xplore Digital Library
Author	Orlando, J.R. Haykin, S.
Copyright Year	1989
Description	Author affiliation: Commun. Res. Lab., McMaster Univ., Hamilton, Ont., Canada (Orlando, J.R.; Haykin, S.)
Abstract	Summary form only given. Experiments performed with dual-polarized Ku-band radar systems have shown that there are distinct differences between the information contained in the like- and cross-polarized returns from the ice floes, particularly between those returns from new and old ice. In order to present the two different images on one monochrome display, it is necessary to combine them. The process can be expedited by using singular-value decomposition (SVD) to determine the eigenvectors, since, in doing so, it is not necessary to compute the covariance matrix explicitly. For the special case of transforming two input images into one output image, the SVD can be computed in a straightforward manner using the rotation matrix of Hestenes (1958). By performing the image transformation using parallel processors, an efficient pipelined architecture for computing the method of principal components can be realized. Such an architecture has been simulated on the Warp systolic computer and applied to the like- and cross-polarized radar images.
Starting Page	53
Ending Page	54
File Size	116752
Page Count	2
File Format	PDF
DOI	10.1109/MDSP.1989.97021
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1989-09-06
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Ice Radar imaging Covariance matrix Computer architecture Navigation Polarization Image generation Arctic Displays Eigenvalues and eigenfunctions
Content Type	Text
Resource Type	Article

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