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On the Mean-Square Error Performance of Adaptive Minimum Variance Beamformers Based on the Sample Covariance Matrix

Publication ,  Journal Article
Krolik, JL; Swingler, DN
Published in: IEEE Transactions on Signal Processing
January 1, 1994

This correspondence examines the mean-square error (MSE) performance of two common implementations of adaptive linearly constrained minimum variance (LCMV) beamformers that employ the sample covariance matrix. The Type I beamformer is representative of block processing methods where the same input data is used both to compute the adaptive weights and to form the beamformer output. The Type II beamformer, as in many recursive schemes, applies adaptive weights computed from previous data to the current input. Due to correlation between the adaptive weights and the input data, the Type I LCMV beamformer exhibits signal cancellation, which is shown here to cause signal estimate bias. To explicitly account for signal cancellation, the mean-square error (MSE) and output signal-to-noise ratio (SNR) measures of the bias-corrected Type I beamformer are analyzed here, thus extending previous results. Further, new analytical results for these performance measures are given for the Type II LCMV beamformer. Comparison of bias-corrected Type I and Type II implementations indicate that both methods yield exactly the same MSE and output SNR performance. © 1994 IEEE

Duke Scholars

Published In

IEEE Transactions on Signal Processing

DOI

EISSN

1941-0476

ISSN

1053-587X

Publication Date

January 1, 1994

Volume

42

Issue

2

Start / End Page

445 / 448

Related Subject Headings

  • Networking & Telecommunications
 

Citation

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Krolik, J. L., & Swingler, D. N. (1994). On the Mean-Square Error Performance of Adaptive Minimum Variance Beamformers Based on the Sample Covariance Matrix. IEEE Transactions on Signal Processing, 42(2), 445–448. https://doi.org/10.1109/78.275625
Krolik, J. L., and D. N. Swingler. “On the Mean-Square Error Performance of Adaptive Minimum Variance Beamformers Based on the Sample Covariance Matrix.” IEEE Transactions on Signal Processing 42, no. 2 (January 1, 1994): 445–48. https://doi.org/10.1109/78.275625.
Krolik JL, Swingler DN. On the Mean-Square Error Performance of Adaptive Minimum Variance Beamformers Based on the Sample Covariance Matrix. IEEE Transactions on Signal Processing. 1994 Jan 1;42(2):445–8.
Krolik, J. L., and D. N. Swingler. “On the Mean-Square Error Performance of Adaptive Minimum Variance Beamformers Based on the Sample Covariance Matrix.” IEEE Transactions on Signal Processing, vol. 42, no. 2, Jan. 1994, pp. 445–48. Scopus, doi:10.1109/78.275625.
Krolik JL, Swingler DN. On the Mean-Square Error Performance of Adaptive Minimum Variance Beamformers Based on the Sample Covariance Matrix. IEEE Transactions on Signal Processing. 1994 Jan 1;42(2):445–448.

Published In

IEEE Transactions on Signal Processing

DOI

EISSN

1941-0476

ISSN

1053-587X

Publication Date

January 1, 1994

Volume

42

Issue

2

Start / End Page

445 / 448

Related Subject Headings

  • Networking & Telecommunications