| Author Name | Affiliation | | Ting Wang | School of Electronic Information Engineering, Hebei University of Technology, Tianjin 300401, China
People’s Liberation Army Air Force 93756, Tianjin 300131, China | | Yi Dong | People’s Liberation Army Air Force 93756, Tianjin 300131, China | | Guofeng Shao | People’s Liberation Army Air Force 93756, Tianjin 300131, China | | Fan Wang | People’s Liberation Army Air Force 93756, Tianjin 300131, China |
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| Abstract: |
| Aiming at the problem that a large number of array elements are needed for uniform arrays to meet the requirements of direction map, a sparse array pattern synthesis method is proposed in this paper based on the sparse sensing theory. First, the Orthogonal Matching Pursuit (OMP) algorithm and the Exact Augmented Lagrange Multiplier (EALM) algorithm were improved in the sparse sensing theory to obtain a more efficient Orthogonal Multi-Matching Pursuit (OMMP) algorithm and the Semi-Exact Augmented Lagrange Multiplier (SEALM) algorithm. Then, the two improved algorithms were applied to linear array and planar array pattern syntheses respectively. Results showed that the improved algorithms could achieve the required pattern with very few elements. Numerical simulations verified the effectiveness and superiority of the two synthetic methods. In addition, compared with the existing sparse array synthesis method, the proposed method was more robust and accurate, and could maintain the advantage of easy implementation. |
| Key words: array antenna compressed sensing low rank matrix recovery Exact Augmented Lagrange Multiplier algorithm |
| DOI：10.11916/j.issn.1005-9113.19018 |
| Clc Number:TN821.91 |
| Fund: |
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| Descriptions in Chinese: |
| 基于稀疏感知的阵列天线方向图综合技术研究 王停1，2，董轶2，邵国峰2，王凡2 （1.河北工业大学 电子信息学院,天津 300401； 2.中国人民解放军93756部队，天津 300131） 中文摘要：针对均匀阵列需要大量的阵元才能满足方向图指标要求的问题，本文基于稀疏感知理论提出稀疏阵列方向图综合的方法。首先，对稀疏感知理论中的信号复原方法OMP(Orthogonal Matching Pursuit)算法和EALM (Exact Augmented Lagrange Multiplier)算法进行改进，提出更高效的OMMP( Orthogonal Multi-Matching Pursuit)算法和SEALM(Semi-Exact Augmented Lagrange Multiplier)算法，然后将两种改进算法分别应用于线阵和平面阵方向图综合。两种算法均可以以非常少的阵元来实现要求的方向图。数值仿真验证了所提出两种合成方法的有效性和优越性。此外，与现有稀疏阵列综合方法相比，本文的方法更加稳健和准确，同时保持了易于实现的优点。 关键字：阵列天线；压缩感知；低秩恢复；精确拉格朗日乘子法 |
