Performance analysis of krylov space adaptive beamformers

Ivars P. Kirsteins; Hongya Ge

doi:10.1109/SAM.2006.1677148

Performance analysis of krylov space adaptive beamformers

Ivars P. Kirsteins, Hongya Ge

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

14 Scopus citations

Abstract

The performance of Krylov subspace-based dimensionality reduction for adaptive beamforming is analyzed using a simple second-order Taylor series approximation to the mean output signal-to-noise ratio (SNR). It is shown that the predicted SNRs accurately follow the experimentally measured SNR and explain the threshold effects when the angles or spacing are varied between the signal mode (subspace) and interference modes (subspace). Furthermore, we discuss how the SNR approximation can be applied to calculating the deflection of a Krylov subspace dimension-reduced Capon's test statistic.

Original language	English (US)
Title of host publication	2006 IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006
Pages	16-20
Number of pages	5
DOIs	https://doi.org/10.1109/SAM.2006.1677148
State	Published - Dec 1 2006
Event	4th IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006 - Waltham, MA, United States Duration: Jul 12 2006 → Jul 14 2006

Other

Other	4th IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006
Country/Territory	United States
City	Waltham, MA
Period	7/12/06 → 7/14/06

All Science Journal Classification (ASJC) codes

Signal Processing
Control and Systems Engineering
Electrical and Electronic Engineering

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10.1109/SAM.2006.1677148

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title = "Performance analysis of krylov space adaptive beamformers",

abstract = "The performance of Krylov subspace-based dimensionality reduction for adaptive beamforming is analyzed using a simple second-order Taylor series approximation to the mean output signal-to-noise ratio (SNR). It is shown that the predicted SNRs accurately follow the experimentally measured SNR and explain the threshold effects when the angles or spacing are varied between the signal mode (subspace) and interference modes (subspace). Furthermore, we discuss how the SNR approximation can be applied to calculating the deflection of a Krylov subspace dimension-reduced Capon's test statistic.",

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doi = "10.1109/SAM.2006.1677148",

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AU - Ge, Hongya

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N2 - The performance of Krylov subspace-based dimensionality reduction for adaptive beamforming is analyzed using a simple second-order Taylor series approximation to the mean output signal-to-noise ratio (SNR). It is shown that the predicted SNRs accurately follow the experimentally measured SNR and explain the threshold effects when the angles or spacing are varied between the signal mode (subspace) and interference modes (subspace). Furthermore, we discuss how the SNR approximation can be applied to calculating the deflection of a Krylov subspace dimension-reduced Capon's test statistic.

AB - The performance of Krylov subspace-based dimensionality reduction for adaptive beamforming is analyzed using a simple second-order Taylor series approximation to the mean output signal-to-noise ratio (SNR). It is shown that the predicted SNRs accurately follow the experimentally measured SNR and explain the threshold effects when the angles or spacing are varied between the signal mode (subspace) and interference modes (subspace). Furthermore, we discuss how the SNR approximation can be applied to calculating the deflection of a Krylov subspace dimension-reduced Capon's test statistic.

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M3 - Conference contribution

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SP - 16

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BT - 2006 IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006

T2 - 4th IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAM 2006

Y2 - 12 July 2006 through 14 July 2006

ER -

Performance analysis of krylov space adaptive beamformers

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