ROBUST ADAPTIVE BEAMFORMING FOR A CLASS OF GAUSSIAN STEERING VECTOR MISMATCH | Zendy

Yujie Gu | Zendy; Zhiguo Shi | Zendy; Kang Sheng Chen | Zendy; Li Yu | Zendy

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ROBUST ADAPTIVE BEAMFORMING FOR A CLASS OF GAUSSIAN STEERING VECTOR MISMATCH

Author(s) -

Yujie Gu,

Zhiguo Shi,

Kang Sheng Chen,

Li Yu

Publication year - 2008

Publication title -

electromagnetic waves

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.437

H-Index - 89

eISSN - 1559-8985

pISSN - 1070-4698

DOI - 10.2528/pier08010202

Subject(s) - adaptive beamformer , class (philosophy) , computer science , gaussian , control theory (sociology) , beamforming , artificial intelligence , telecommunications , physics , control (management) , quantum mechanics

—Compared with the worst-case optimization-based ap- proach, the probability-constrained approach is a more flexible one to robust adaptive beamforming. In this paper, a precise relationship between the two approaches is built in the case of Gaussian steering vector mismatch, which shows that the probability-constrained beam- former design can be interpreted in terms of the worst-case beamformer design. Numerical simulations demonstrate that the precise version of the probability-constrained beamformer is more robust to the steering vector mismatch than the other popular robust adaptive beamformers.

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