| Paper: | SAM-P3.1 | ||
| Session: | Beamforming and Space-Time Processing | ||
| Time: | Wednesday, May 17, 10:00 - 12:00 | ||
| Presentation: | Poster | ||
| Topic: | Sensor Array and Multichannel Signal Processing: Signal detection and estimation | ||
| Title: | Adaptive Bayesian Beamforming for Steering Vector Uncertainties with Order Recursive Implementation | ||
| Authors: | Chunwei Jethro Lam, Andrew Singer, University of Illinois at Urbana-Champaign, United States | ||
| 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). | ||
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