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基于矢量最优化的稳健波束形成方法
引用本文:宋海岩,朴胜春,秦进平. 基于矢量最优化的稳健波束形成方法[J]. 兵工学报, 2012, 33(10): 1222-1229
作者姓名:宋海岩  朴胜春  秦进平
作者单位:(1.黑龙江工程学院 电气与信息工程学院, 黑龙江 哈尔滨 150050;2.哈尔滨工程大学 水声工程学院黑龙江 哈尔滨 150001)
摘    要:当阵列导向矢量存在误差或接收信号采样样本数较少时,标准Capon波束形成(SCB)的性能会严重退化。现有的提高稳健性的算法大都是针对导向矢量误差而提出的,很少考虑有限采样效应条件下的稳健性问题。针对以上原因,从导向矢量误差和有限采样效应两个角度出发,引入矢量最优化概念,提出了基于矢量最优化的稳健波束形成(VORB)方法,进而提高SCB算法的稳健性,并通过二阶锥(SOC)规划理论对其进行求解。文中还进一步推导了自适应权矢量的近似解析表达式,揭示了影响最优权矢量的各主要因素之间的关系,同时证明了该算法广义上属于对角加载类方法。通过理论分析和计算机仿真研究,表明了VORB方法对自适应波束形成算法的稳健性有明显的改善:在不同快拍数、信噪比(SNR)和导向矢量不确定度条件下,VORB方法的输出信干噪比(SINR)均较其他算法提高约5 dB;在典型工况条件下,VORB具有更尖锐的谱峰,更低的旁瓣级(低至-15 dB以下)。外场试验数据处理结果表明,将VORB应用于实际工程进行空间谱估计,能够得到准确而稳健的高分辨方位估计结果。

关 键 词:信息处理技术   稳健自适应波束形成   矢量最优化   正则化   二阶锥规划  
收稿时间:2010-10-27

Robust Adaptive Beamforming Based on Vector Optimization
SONG Hai-yan , PIAO Sheng-chun , QIN Jin-ping. Robust Adaptive Beamforming Based on Vector Optimization[J]. Acta Armamentarii, 2012, 33(10): 1222-1229
Authors:SONG Hai-yan    PIAO Sheng-chun    QIN Jin-ping
Affiliation:(1.School of Electrical and Information Engineering, Heilongjiang Institute of Technology, Harbin 150050, Heilongjiang, China;2.Underwater Acoustic Engineering Department, Harbin Engineering University, Harbin 150001, Heilongjiang, China)
Abstract:When an arbitrary unknown signal steering vector mismatch occurs or the training sample size is small, the performance of standard Capon beamforming (SCB) will be severely degraded. The existing algorithms are mostly made for the steering vector errors, with little considering the situations of small training sample size. In this paper, we develop a new approach, which is called vector optimization robust beamforming (VORB), to robust adaptive beamforming in the presence of an arbitrary unknown signal steering vector mismatch and small training sample size. Our approach is based on the vector optimization concept. It is shown that the proposed algorithm can be reformulated in a convex form as the so-called second-order cone (SOC) program and solved efficiently using the well-established optimization tool, Sedumi. It is also shown that the proposed technique can be interpreted in terms of diagonal loading, and how the optimization value of the diagonal loading is affected by different factors. Theory analysis and computer simulations show better performance of our robust beamformer as compared with existing adaptive beamforming algorithms: under different snapshots, SNRs and steering vector uncertainties, VORB can improve the output SINRs about 5 dB; under certain conditions, VORB has sharper spectrum peaks and lower sidelobe level (below -15 dB). Finally, experimental results show that when VORB is applied to the spatial spectrum estimation in practical engineering, the robust high-resolution bearing estimation results can be obtained.
Keywords:
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