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Minimum sensitivity based robust beamforming with eigenspace decomposition

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Abstract

An enhanced eigenspace-based beamformer (ESB) derived using the minimum sensitivity criterion is proposed with significantly improved robustness against steering vector errors. The sensitivity function is defined as the squared norm of the appropriately scaled weight vector and since the sensitivity function of an array to perturbations becomes very large in the presence of steering vector errors, it can be used to find the best projection for the ESB, irrespective of the distribution of additive noises. As demonstrated by simulation results, the proposed method has a better performance than the classic ESBs and the previously proposed uncertainty set based approach.

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Authors and Affiliations

  1. School of Electronic Information Engineering, Beijing Jiaotong University, Beijing, 100044, China

    Jun Wang

  2. Science and Technology on Electronic Information Control Laboratory, Chengdu, 610036, China

    Wei Zhang

  3. Communications Research Group, Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield, S1 3JD, UK

    Wei Liu

Authors
  1. Jun Wang
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  2. Wei Zhang
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  3. Wei Liu
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Correspondence to Wei Liu.

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Wang, J., Zhang, W. & Liu, W. Minimum sensitivity based robust beamforming with eigenspace decomposition. Multidim Syst Sign Process 29, 687–701 (2018). https://doi.org/10.1007/s11045-016-0424-1

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  • DOI: https://doi.org/10.1007/s11045-016-0424-1

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