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2013-09-02

Modified Bayesian Beamformer for Binning Error Elimination

By Said El-Khamy, Mohammed Rizk Rizk, and Roshdy K. Korayem
Progress In Electromagnetics Research C, Vol. 43, 121-133, 2013
doi:10.2528/PIERC13070702

Abstract

Constrained Least Mean Square (CLMS) algorithm is used to adapt the antenna array weights. CLMS in its simple form fails to capture the Signal of Interest (SOI) if there is an error in the Direction of Arrival (DOA) estimation. Moreover, it will consider the SOI as an interferer and create null in the desired DOA. The large gain will be towards the detected wrong direction. Derivative constraints and Bayesian beamformer are two techniques used to overcome such a problem. Derivative constraints destroy a lot of Degrees of Freedom (DOF). Bayesian beamformer destroys only one DOF but vulnerable to binning error. The proposed algorithm overcomes the problem of binning error in the Bayesian beamformer with only one extra DOF.

Citation


Said El-Khamy, Mohammed Rizk Rizk, and Roshdy K. Korayem, "Modified Bayesian Beamformer for Binning Error Elimination," Progress In Electromagnetics Research C, Vol. 43, 121-133, 2013.
doi:10.2528/PIERC13070702
http://www.jpier.org/PIERC/pier.php?paper=13070702

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