New Designs on MVDR Robust Adaptive Beamforming Based on Optimal Steering Vector Estimation

The robust adaptive beamforming design problem based on estimation of the signal-of-interest (SOI) steering vector is considered in the paper. The common criteria to find the best estimate of the steering vector are the beamformer output signal-to-noise-plus-interference ratio (SINR) and output powe...

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Vydáno v:IEEE transactions on signal processing Ročník 67; číslo 14; s. 3624 - 3638
Hlavní autoři: Yongwei Huang, Mingkang Zhou, Vorobyov, Sergiy A.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 15.07.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Antenna arrays
Antennas
Array signal processing
Beamforming
Computer simulation
Constraints
Covariance matrices
Direction of arrival
efficient algorithms
Estimation
Interference
Mathematical analysis
Maximization
Minimum variance distortionless response
non-convex quadratically constrained quadratic programming
optimal steering vector estimation
Optimization
Power generation
Quadratic programming
robust adaptive beamforming
Robustness
Signal to noise ratio
Similarity
Steering
ISSN:1053-587X, 1941-0476
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Shrnutí:The robust adaptive beamforming design problem based on estimation of the signal-of-interest (SOI) steering vector is considered in the paper. The common criteria to find the best estimate of the steering vector are the beamformer output signal-to-noise-plus-interference ratio (SINR) and output power, while the constraints assume as little as possible prior inaccurate knowledge about the SOI, the propagation media, and the antenna array. Herein, in order to find the optimal steering vector, a beamformer output power maximization problem is formulated and solved subject to a double-sided norm perturbation constraint, a similarity constraint, and a quadratic constraint that guarantees that the direction-of-arrival (DOA) of the SOI is away from the DOA region of all linear combinations of the interference steering vectors. The prior knowledge required is some allowable error norm bounds and approximate knowledge of the antenna array geometry and angular sector of the SOI. It turns out that the array output power maximization problem is a non-convex quadratically constrained quadratic programming problem with inhomogeneous constraints. However, we show that the problem is still solvable, and develop efficient algorithms for finding globally optimal estimate of the SOI steering vector. The results are generalized to the case when an ellipsoidal constraint is considered instead of the similarity constraint, and sufficient conditions for the global optimality are derived. In addition, a new quadratic constraint on the actual signal steering vector is proposed in order to improve the array performance. To validate our results, simulation examples are presented, and they demonstrate the improved performance of the new robust beamformers in terms of the output SINR as well as the output power.
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ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2019.2918997