Efficient Adaptive Subspace Tracking Algorithm for Automatic Target Recognition

P. Ragothaman, T. Yang, W. Mikhael, R. Muise, A. Mahalanobis

Research output: Contribution to journalArticlepeer-review

Abstract

Automatic target recognition using quadratic correlation filters has been reported recently. It requires the eigenvalue decomposition (EVD) of a large matrix computed using the autocorrelation matrices of target and clutter training images. In practice, situations arise where new images need to be incorporated, which perturbs the EVD. Proposed is a novel computationally efficient method to obtain the new EVD adaptively. Sample results using an infrared dataset illustrate the effectiveness of the technique. © The Institution of Engineering and Technology 2006.

Original languageAmerican English
JournalIET Electronics Letters
Volume42
DOIs
StatePublished - Oct 9 2006

Disciplines

  • Signal Processing

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