An Improved Passive Synthetic Aperture Algorithm Based on Curvilinear Maneuverability of Autonomous Underwater Vehicles
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摘要: 水下自主无人平台(AUV)在曲线机动情况下利用传统ETAM方法扩展孔径时，目标方位估计结果无法聚焦到真实方位，估计偏差严重，针对这一问题，该文结合运动补偿提出一种新的ETAM算法。该算法将波束域与阵元域结合处理，在波束域获取相位信息，在阵元域对相位信息进行线性拟合，有效克服曲线运动造成的相位误差，得到相位修正因子后对连续测量进行相位补偿，实现孔径扩展。仿真和试验结果表明，无论平台直线航行还是曲线机动，该算法在对比算法失效的情况下，仍具有很高的测向精度、角度分辨率及空间增益，且适用于多目标的分辨，在较低信噪比下对性能的改善更为明显，有较强的实用性和环境宽容性。Abstract: In order to overcome difficulty in extending flank array by traditional Extended Towed Array Measurement (ETAM) technique based on curvilinear maneuverability of Autonomous Underwater Vehicles (AUV), a new ETAM method is proposed by combining estimating phase correction factors in beam domain and linear fitting motion compensation in element domain. The method estimates phase differences in beam domain and implements linear fitting of phase correction factors in element domain to compensate phase error due to curvilinear motion, which can acquire accurate phase correction factors and extend array. Results of simulation and experiment show that no matter straight line navigation or curvilinear maneuverability, the method achieved higher DOA estimation accuracy, angular resolution and signal gain, which is also suitable for multi-target resolving. Especially in low signal-noise-ratio condition, the improvement of this method in performance is more obvious, for which it has strong practicality and environmental tolerance.
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