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Relationships between adaptive minimum variance beamforming and optimal source localization

Publication ,  Journal Article
Harmanci, K; Tabrikian, J; Krolik, JL
Published in: IEEE Transactions on Signal Processing
January 1, 2000

For many years, the popular minimum variance (MV) adaptive beamformer has been well known for not having been derived as a maximum likelihood (ML) estimator. This paper demonstrates that by use of a judicious decomposition of the signal and noise, the log-likelihood function of source location is, in fact, directly proportional to the adaptive MV beamformer output power. In the proposed model, the measurement consists of an unknown temporal signal whose spatial wavefront is known as a function of its unknown location, which is embedded in complex Gaussian noise with unknown but positive definite covariance. Further, in cases where the available observation time is insufficient, a constrained ML estimator is derived here that is closely related to MV beamforming with a diagonally loaded data covariance matrix estimate. The performance of the constrained ML estimator compares favorably with robust MV techniques, giving slightly better root-mean-square error (RMSE) angle-of-arrival estimation of a plane-wave signal in interference. More importantly, however, the fact that such optimal ML techniques are closely related to conventional robust MV methods, such as diagonal loading, lends theoretical justification to the use of these practical approaches.

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Published In

IEEE Transactions on Signal Processing

DOI

ISSN

1053-587X

Publication Date

January 1, 2000

Volume

48

Issue

1

Start / End Page

1 / 12

Related Subject Headings

  • Networking & Telecommunications
 

Citation

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Harmanci, K., Tabrikian, J., & Krolik, J. L. (2000). Relationships between adaptive minimum variance beamforming and optimal source localization. IEEE Transactions on Signal Processing, 48(1), 1–12. https://doi.org/10.1109/78.815474
Harmanci, K., J. Tabrikian, and J. L. Krolik. “Relationships between adaptive minimum variance beamforming and optimal source localization.” IEEE Transactions on Signal Processing 48, no. 1 (January 1, 2000): 1–12. https://doi.org/10.1109/78.815474.
Harmanci K, Tabrikian J, Krolik JL. Relationships between adaptive minimum variance beamforming and optimal source localization. IEEE Transactions on Signal Processing. 2000 Jan 1;48(1):1–12.
Harmanci, K., et al. “Relationships between adaptive minimum variance beamforming and optimal source localization.” IEEE Transactions on Signal Processing, vol. 48, no. 1, Jan. 2000, pp. 1–12. Scopus, doi:10.1109/78.815474.
Harmanci K, Tabrikian J, Krolik JL. Relationships between adaptive minimum variance beamforming and optimal source localization. IEEE Transactions on Signal Processing. 2000 Jan 1;48(1):1–12.

Published In

IEEE Transactions on Signal Processing

DOI

ISSN

1053-587X

Publication Date

January 1, 2000

Volume

48

Issue

1

Start / End Page

1 / 12

Related Subject Headings

  • Networking & Telecommunications