<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper addresses the self-nulling phenomenon also known as the self-cancellation in adaptive beamformers. Optimum beamforming requires knowledge of the desired signal characteristics, either its statistics, its direction-of-arrival, or its response vector. Inaccuracies in the required information lead the beamformer to attenuate the desired signal as if it were interference. Self-nulling is caused by the desired signal having large power (high SNR) relative to the interference signal in case of the minimum variance distortion less response beamformer, and low power desired signal in the case of the constant modulus algorithm (CMA) beamformer, which leads the beamformer to suppress the desired signal and lock onto the interference signal. The least-square constant modulus algorithm is a prominent blind adaptive beamforming algorithm. We propose two CMA-based algorithms which exploit the constant modularity as well as power or DOA of the desired signal to avoid self-nulling in beamforming. Simulations results verify the effectiveness of the proposed algorithms.</p>
</abstract>

This paper addresses the self-nulling phenomenon also known as the self-cancellation in adaptive beamformers. Optimum beamforming requires knowledge of the desired signal characteristics, either its statistics, its direction-of-arrival, or its response vector. Inaccuracies in the required information lead the beamformer to attenuate the desired signal as if it were interference. Self-nulling is caused by the desired signal having large power (high SNR) relative to the interference signal in case of the minimum variance distortion less response beamformer, and low power desired signal in the case of the constant modulus algorithm (CMA) beamformer, which leads the beamformer to suppress the desired signal and lock onto the interference signal. The least-square constant modulus algorithm is a prominent blind adaptive beamforming algorithm. We propose two CMA-based algorithms which exploit the constant modularity as well as power or DOA of the desired signal to avoid self-nulling in beamforming. Simulations results verify the effectiveness of the proposed algorithms.

Robust adaptive beamforming using modified constant modulus algorithms

Department of Physics, Division of Science and Technology

Journal of Electrical Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Robust adaptive beamforming using modified constant modulus algorithms"}

This paper addresses the self-nulling phenomenon also known as the self-cancellation in adaptive beamformers. Optimum beamforming requires knowledge of the...

Robust adaptive beamforming using modified constant modulus algorithms

Published Online: Sep 22, 2022

Page range: 248 - 257

Received: Jul 01, 2022

DOI: https://doi.org/10.2478/jee-2022-0033

Keywords
array signal processing, constant modulus algorithm, robust adaptive beamforming, self-nulling

© 2022 Zeeshan Ahmad et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Robust adaptive beamforming using modified constant modulus algorithms

Published Online: Sep 22, 2022

Page range: 248 - 257

Received: Jul 01, 2022

DOI: https://doi.org/10.2478/jee-2022-0033

Keywordsarray signal processing, constant modulus algorithm, robust adaptive beamforming, self-nulling

© 2022 Zeeshan Ahmad et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Keywords
array signal processing, constant modulus algorithm, robust adaptive beamforming, self-nulling