Adaptive Beamforming Based on Compressed Sensing with Smoothed l0 Norm
An adaptive beamforming based on compressed sensing with smoothed l0 norm for large-scale sparse receiving array is proposed in this paper. Because of the spatial sparsity of the arriving signal, compressed sensing is applied to sample received signals with a sparse array and reduced channels. The s...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-01-01
|
| Series: | International Journal of Antennas and Propagation |
| Online Access: | http://dx.doi.org/10.1155/2015/959856 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850216403002458112 |
|---|---|
| author | Yubing Han Jian Wang |
| author_facet | Yubing Han Jian Wang |
| author_sort | Yubing Han |
| collection | DOAJ |
| description | An adaptive beamforming based on compressed sensing with smoothed l0 norm for large-scale sparse receiving array is proposed in this paper. Because of the spatial sparsity of the arriving signal, compressed sensing is applied to sample received signals with a sparse array and reduced channels. The signal of full array is reconstructed by using a compressed sensing reconstruction method based on smoothed l0 norm. Then an iterative linearly constrained minimum variance beamforming algorithm is adopted to form antenna beam, whose main lobe is steered to the desired direction and nulls to the directions of interferences. Simulation results and Monte Carlo analysis for linear and planar arrays show that the beam performances of our proposed adaptive beamforming are similar to those of full array antenna. |
| format | Article |
| id | doaj-art-3c4029e8b42e433b8e6953edc2a92955 |
| institution | OA Journals |
| issn | 1687-5869 1687-5877 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Antennas and Propagation |
| spelling | doaj-art-3c4029e8b42e433b8e6953edc2a929552025-08-20T02:08:19ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772015-01-01201510.1155/2015/959856959856Adaptive Beamforming Based on Compressed Sensing with Smoothed l0 NormYubing Han0Jian Wang1School of Electronic and Optical Engineering, Nanjing University of Science & Technology, Nanjing 210094, ChinaSchool of Electronic and Optical Engineering, Nanjing University of Science & Technology, Nanjing 210094, ChinaAn adaptive beamforming based on compressed sensing with smoothed l0 norm for large-scale sparse receiving array is proposed in this paper. Because of the spatial sparsity of the arriving signal, compressed sensing is applied to sample received signals with a sparse array and reduced channels. The signal of full array is reconstructed by using a compressed sensing reconstruction method based on smoothed l0 norm. Then an iterative linearly constrained minimum variance beamforming algorithm is adopted to form antenna beam, whose main lobe is steered to the desired direction and nulls to the directions of interferences. Simulation results and Monte Carlo analysis for linear and planar arrays show that the beam performances of our proposed adaptive beamforming are similar to those of full array antenna.http://dx.doi.org/10.1155/2015/959856 |
| spellingShingle | Yubing Han Jian Wang Adaptive Beamforming Based on Compressed Sensing with Smoothed l0 Norm International Journal of Antennas and Propagation |
| title | Adaptive Beamforming Based on Compressed Sensing with
Smoothed l0 Norm |
| title_full | Adaptive Beamforming Based on Compressed Sensing with
Smoothed l0 Norm |
| title_fullStr | Adaptive Beamforming Based on Compressed Sensing with
Smoothed l0 Norm |
| title_full_unstemmed | Adaptive Beamforming Based on Compressed Sensing with
Smoothed l0 Norm |
| title_short | Adaptive Beamforming Based on Compressed Sensing with
Smoothed l0 Norm |
| title_sort | adaptive beamforming based on compressed sensing with smoothed l0 norm |
| url | http://dx.doi.org/10.1155/2015/959856 |
| work_keys_str_mv | AT yubinghan adaptivebeamformingbasedoncompressedsensingwithsmoothedl0norm AT jianwang adaptivebeamformingbasedoncompressedsensingwithsmoothedl0norm |