### Abstract

An order recursive algorithm for minimum mean square error (MMSE) estimation of signals under a Bayesian model defined on the steering vector is introduced. The MMSE estimate can be viewed as a mixture of conditional MMSE estimates weighted by the posterior probability density function (PDF) of the random steering vector given the observed data. This paper derives an adaptive closed form Kalman-filter implementation that updates the weight vector by successive incorporations of data collected from additional array elements in the steering vector. The performance of the Bayesian beamformer is compared against several robust beamformers in terms of mean square error (MSE) and output signal-to-interference-plus-noise ratio (SINR).

Original language | English (US) |
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Title of host publication | 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings |

Pages | IV997-IV1000 |

State | Published - Dec 1 2006 |

Event | 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006 - Toulouse, France Duration: May 14 2006 → May 19 2006 |

### Publication series

Name | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
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Volume | 4 |

ISSN (Print) | 1520-6149 |

### Other

Other | 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006 |
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Country | France |

City | Toulouse |

Period | 5/14/06 → 5/19/06 |

### Fingerprint

### ASJC Scopus subject areas

- Software
- Signal Processing
- Electrical and Electronic Engineering

### Cite this

*2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings*(pp. IV997-IV1000). [1661139] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 4).

**Adaptive bayesian beamforming for steering vector uncertainties with order recursive implementation.** / Lam, Chunwei Jethro; Singer, Andrew C.

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

*2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings.*, 1661139, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 4, pp. IV997-IV1000, 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006, Toulouse, France, 5/14/06.

}

TY - GEN

T1 - Adaptive bayesian beamforming for steering vector uncertainties with order recursive implementation

AU - Lam, Chunwei Jethro

AU - Singer, Andrew C.

PY - 2006/12/1

Y1 - 2006/12/1

N2 - An order recursive algorithm for minimum mean square error (MMSE) estimation of signals under a Bayesian model defined on the steering vector is introduced. The MMSE estimate can be viewed as a mixture of conditional MMSE estimates weighted by the posterior probability density function (PDF) of the random steering vector given the observed data. This paper derives an adaptive closed form Kalman-filter implementation that updates the weight vector by successive incorporations of data collected from additional array elements in the steering vector. The performance of the Bayesian beamformer is compared against several robust beamformers in terms of mean square error (MSE) and output signal-to-interference-plus-noise ratio (SINR).

AB - An order recursive algorithm for minimum mean square error (MMSE) estimation of signals under a Bayesian model defined on the steering vector is introduced. The MMSE estimate can be viewed as a mixture of conditional MMSE estimates weighted by the posterior probability density function (PDF) of the random steering vector given the observed data. This paper derives an adaptive closed form Kalman-filter implementation that updates the weight vector by successive incorporations of data collected from additional array elements in the steering vector. The performance of the Bayesian beamformer is compared against several robust beamformers in terms of mean square error (MSE) and output signal-to-interference-plus-noise ratio (SINR).

UR - http://www.scopus.com/inward/record.url?scp=33947614575&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33947614575&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:33947614575

SN - 142440469X

SN - 9781424404698

T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

SP - IV997-IV1000

BT - 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings

ER -