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自适应波束域被动合成孔径技术研究

Research on passive synthetic aperture technique in adaptive beam space

  • 摘要: 被动合成孔径声纳技术(passive synthetic aperture sonar,PSAS),利用基阵的运动拓展虚拟阵元形成大孔径基阵,能显著提高目标方位分辨力和弱目标探测能力。传统阵元域扩展拖曳阵方法ETAM(extended towed array measurements,ETAM )在阵元域估计相位修正因子,低信噪比时性能较差。本文将自适应波束形成与波束域ETAM合成孔径方法结合,在子阵波束域估计相位修正因子并进行自适应波束形成。仿真和试验数据表明,本方法相比传统阵元域ETAM方法方位分辨率和输出信噪比分别提高1.5°和4.6dB,低信噪比情况下性能稳健,为基于运动平台的被动弱目标探测提供了有力支撑。

     

    Abstract: Passive Synthetic Aperture Sonar (PSAS), which uses the motion of the array to expand the virtual array to form a large aperture array, can significantly improve the azimuth resolution and weak target detection ability. The traditional Extended Towed Array Measurements (ETAM) method can estimate the phase correction factor in the array domain, but its performance is poor at low signal-to-noise ratio. In this paper, adaptive beamforming and ETAM synthetic aperture methods are combined to estimate the phase correction factor in the subarray beam space and perform adaptive beamforming. The simulation and experimental data show that the azimuth resolution and output signal-to-noise (SNR) ratio of the proposed method are 1.5° and 4.6 dB higher than those of the traditional ETAM method, and it is robust at low SNR and multiple targets, which provides strong support for passive weak target detection based on moving platforms.

     

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