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Robust Adaptive Broadband Beamforming Based on Constraints Magnitude Response

Luo Jing-qing

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Abstract

The performance of adaptive beamforming algorithms is known to undergo substantial degradation in the presence of even slight steering direction error.To account for mismatches,a novel robust adaptive broadband beamforming algorithm based on constraints magnitude response(CMR) was proposed.An array magnitude response constraint over the region around the array steering direction was used to increase the robustness of the optimal beamforming against steering direction mismatch.Combined with the frequency invariant technique,the array beampatten kept approximately the same amplitude response to the wideband incident signal at different frequencies.The weight vector was optimized to involve minimization of a quadratic function subject to constraint on magnitude response at the reference frequency.Simulation results demonstrated that,compared with the worst-case optimization method,the algorithm had low complexity and was able to flexibly control the robust response region with specified beamwidth and response ripple.Furthermore,the proposed beam former could obtain the prescribed robustness against steering vector errors,suffered the least distortion from the directions near the steering angle,improved the output array signal-to-interference-plus-noise ratio(SINR) performance,and made SINR consistently close to the optimal one.

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The performance of adaptive beamforming algorithms is known to undergo substantial degradation in the presence of even slight steering direction error.To account for mismatches,a novel robust adaptive broadband beamforming algorithm based on constraints magnitude response(CMR) was proposed.An array magnitude response constraint over the region around the array steering direction was used to increase the robustness of the optimal beamforming against steering direction mismatch.Combined with the frequency invariant technique,the array beampatten kept approximately the same amplitude response to the wideband incident signal at different frequencies.The weight vector was optimized to involve minimization of a quadratic function subject to constraint on magnitude response at the reference frequency.Simulation results demonstrated that,compared with the worst-case optimization method,the algorithm had low complexity and was able to flexibly control the robust response region with specified beamwidth and response ripple.Furthermore,the proposed beam former could obtain the prescribed robustness against steering vector errors,suffered the least distortion from the directions near the steering angle,improved the output array signal-to-interference-plus-noise ratio(SINR) performance,and made SINR consistently close to the optimal one.

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Available abstract

The performance of adaptive beamforming algorithms is known to undergo substantial degradation in the presence of even slight steering direction error.To account for mismatches,a novel robust adaptive broadband beamforming algorithm based on constraints magnitude response(CMR) was proposed.An array magnitude response constraint over the region around the array steering direction was used to increase the robustness of the optimal beamforming against steering direction mismatch.Combined with the frequency invariant technique,the array beampatten kept approximately the same amplitude response to the wideband incident signal at different frequencies.The weight vector was optimized to involve minimization of a quadratic function subject to constraint on magnitude response at the reference frequency.Simulation results demonstrated that,compared with the worst-case optimization method,the algorithm had low complexity and was able to flexibly control the robust response region with specified beamwidth and response ripple.Furthermore,the proposed beam former could obtain the prescribed robustness against steering vector errors,suffered the least distortion from the directions near the steering angle,improved the output array signal-to-interference-plus-noise ratio(SINR) performance,and made SINR consistently close to the optimal one.

Key concepts: Beamforming, Beamwidth, Adaptive beamformer, Robustness (evolution), Control theory (sociology), Computer science, Signal-to-interference-plus-noise ratio, Algorithm

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