2002Unpublished venueRequires access

Direction finding for wideband signals using fast coherent signal subspace

Miloud Frikel, Salah Bourennane

Open publisher page 1 citations

Abstract

A method to estimate the set of bias vectors spanning the signal subspace without eigendecomposition is described. Each basis vector can be determined by the Lanczos algorithm. The signal subspace estimates at each frequency are transformed by focusing matrices such that the coherent signal subspace will be constructed for all analysis bands. The performance of the proposed method is shown to be almost the same as that of the classical eigendecomposition method.

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What this paper is about

A method to estimate the set of bias vectors spanning the signal subspace without eigendecomposition is described. Each basis vector can be determined by the Lanczos algorithm. The signal subspace estimates at each frequency are transformed by focusing matrices such that the coherent signal subspace will be constructed for all analysis bands. The performance of the proposed method is shown to be almost the same as that of the classical eigendecomposition method.

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Available abstract

A method to estimate the set of bias vectors spanning the signal subspace without eigendecomposition is described. Each basis vector can be determined by the Lanczos algorithm. The signal subspace estimates at each frequency are transformed by focusing matrices such that the coherent signal subspace will be constructed for all analysis bands. The performance of the proposed method is shown to be almost the same as that of the classical eigendecomposition method.

Key concepts: Signal subspace, Eigendecomposition of a matrix, Subspace topology, Wideband, Lanczos resampling, SIGNAL (programming language), Algorithm, Signal processing

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