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New versions of the propagator method

Mohamed Bouri

Open publisher page 2 citations

Abstract

In this paper, we introduce new technique for localization of narrowband signals. We propose two new versions of the propagator method. Using its algebraic properties, the cross-spectral matrix (CSM) is replaced by the upper triangular matrix (UTM) obtained from the LU or QR factorization of the CSM. The upper triangular matrices are partitioned to estimate the propagator. The LU factorization and Householder QR factorization algorithms need N3/3 and 2N3/3 floating point operations, respectively. The triangular factorization technique can reduce the complexity when compared to eigen subspace method such as MUSIC algorithm requires N3. Simulation results are presented to verify the effectiveness of the proposed methods.

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What this paper is about

In this paper, we introduce new technique for localization of narrowband signals. We propose two new versions of the propagator method. Using its algebraic properties, the cross-spectral matrix (CSM) is replaced by the upper triangular matrix (UTM) obtained from the LU or QR factorization of the CSM. The upper triangular matrices are partitioned to estimate the propagator. The LU factorization and Householder QR factorization algorithms need N3/3 and 2N3/3 floating point operations, respectively. The triangular factorization technique can reduce the complexity when compared to eigen subspace method such as MUSIC algorithm requires N3. Simulation results are presented to verify the effectiveness of the proposed methods.

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Available abstract

In this paper, we introduce new technique for localization of narrowband signals. We propose two new versions of the propagator method. Using its algebraic properties, the cross-spectral matrix (CSM) is replaced by the upper triangular matrix (UTM) obtained from the LU or QR factorization of the CSM. The upper triangular matrices are partitioned to estimate the propagator. The LU factorization and Householder QR factorization algorithms need N3/3 and 2N3/3 floating point operations, respectively. The triangular factorization technique can reduce the complexity when compared to eigen subspace method such as MUSIC algorithm requires N3. Simulation results are presented to verify the effectiveness of the proposed methods.

Key concepts: Factorization, Propagator, Triangular matrix, Matrix decomposition, QR decomposition, Subspace topology, Computer science, Algebraic number

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