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| Adaptive Beam-forming Algorithm with Subspace Reconstructing |
| Yang Zhi-wei① He Shun①② Liao Gui-sheng① Liu Nan① |
①(National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China)
②(Communication and Information Engineering Collage, Xi'an University of Science and Technology, Xi'an 710054, China) |
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Abstract Considering the issue that full-dimensional adaptive beam-forming takes usually a large number of sampling data and has very high computation cost by using Sample Matrix Inverse (SMI) algorithm, a new adaptive Beam-Forming algorithm based on Subspace ReConstructing (SRC-BF) is proposed in this paper. Illuminated by the multi-dimensional array data having the characteristics of reconstruction of fractal-dimension, the proposed approach is carried out in three stages. Firstly, the fractal-dimensional signal subspace of the array data is estimated using training samples; Secondly, the full-dimensional signal subspace is reconstructed by adopting the tensor product operation and the cross terms is removed adaptively; Finally, the beam-forming weight vector is deduced by the subspace projection algorithm. Theoretical analysis and simulation results show that the method has lower computational complexity and can effectively improve the output Signal-to- Interference-plus-Noise Ration (SINR) with the small sample support.
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Received: 29 August 2011
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Corresponding Authors:
Yang Zhi-wei
E-mail: zwyang@mail.xidian.edu.cn
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2012, Vol. 34 
