Pattern Synthesis for Sparse Arrays by Compressed Sensing and Low-Rank Matrix Recovery Methods
| Autor: | Ke-Wen Xia, Ning Lu, Ting Wang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Article Subject
Computer science Smart antenna 020206 networking & telecommunications Low-rank approximation 02 engineering and technology lcsh:HE9713-9715 Directivity Antenna array Compressed sensing Sparse array 0202 electrical engineering electronic engineering information engineering Electronic engineering Miniaturization lcsh:Cellular telephone services industry. Wireless telephone industry 020201 artificial intelligence & image processing lcsh:Electrical engineering. Electronics. Nuclear engineering Electrical and Electronic Engineering Antenna (radio) lcsh:TK1-9971 |
| Zdroj: | International Journal of Antennas and Propagation, Vol 2018 (2018) |
| ISSN: | 1687-5877 1687-5869 |
| Popis: | Antenna array pattern synthesis technology plays a vital role in the field of smart antennas. It is well known that the pattern synthesis of homogeneous array is the key topic of pattern synthesis technology. But this technology needs plenty of homogeneous array elements to meet the antenna requirements. So, a novel pattern synthesis technology for sparse array based on the compressed sensing (CS) and low-rank matrix recovery (LRMR) methods is proposed. The proposed technology predominantly includes the design of sparse array, the recovery of homogeneous array, and the synthesis of antenna array pattern. The simulation result shows that an antenna array with low gain and strong directivity can be arbitrarily built by the use of a small amount of sparse array elements and it is useful for the miniaturization and economical efficiency of the antenna system. |
| Databáze: | OpenAIRE |
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