Adaptive determination of eigenvalues and eigenvectors from perturbed autocorrelation matrices for automatic target recognition
Pradeep Ragothaman, Wasfy B. Mikhael, Robert Muise, Abhijit Mahalanobis, Tianruo Yang · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
The Modified Eigenvalue problem arises in many applications such as Array Processing, Automatic Target Recognition (ATR), etc. These applications usually involve the Eigenvalue Decomposition (EVD) of matrices that are time varying. It is desirable to have methods that eliminate the need to perform an EVD every time the matrix changes but instead update the EVD adaptively, starting from the initial EVD. In this paper, we propose a novel Optimal Adaptive Algorithm for the Modified EVD problem (OAMEVD). Sample results are presented for an ATR application, which uses Rayleigh Quotient Quadratic Correlation filters (RQQCF). Using a Infrared (IR) dataset, the effectiveness of this new technique as well as its advantages are illustrated.