Time-Varying Spectrum Estimation Via Multidimensional Filter Representation

Moeness G. Amin; Maryanne T. Schiavoni

doi:10.1117/12.962297

14 November 1989 Time-Varying Spectrum Estimation Via Multidimensional Filter Representation

Moeness G. Amin, Maryanne T. Schiavoni

Proceedings Volume 1152, Advanced Algorithms and Architectures for Signal Processing IV; (1989) https://doi.org/10.1117/12.962297
Event: 33rd Annual Technical Symposium, 1989, San Diego, United States

Abstract

Smoothing of Wigner distribution introduces two dimensional sequences which brings the theory of two-dimensional filter analysis and design to the one-dimensional time-varying spectrum estimation. In this paper, the region of support of the 2-D filters associated with the commonly used periodogram, averaged periodograms and Wigner estimators are defined and used to express through the singular value decomposition, the periodograms-based estimators as a linear combination of the Pseudo Wigner estimators (PWE). The PWE associated with the maximum singular value of the eigenvector expansion of the periodogram is viewed as the closest approximation between the two estimators. Error bounds are derived and simulations are performed to demonstrate the effects of limiting the expansion to the dominant singular vale es, i.e., using a reduced rank periodogram.

Citation Download Citation

Moeness G. Amin and Maryanne T. Schiavoni "Time-Varying Spectrum Estimation Via Multidimensional Filter Representation", Proc. SPIE 1152, Advanced Algorithms and Architectures for Signal Processing IV, (14 November 1989); https://doi.org/10.1117/12.962297

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