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针对现有方法在侧扫声呐水柱区图像受发射脉冲、海面回波、尾流及大面积悬浮物等干扰情况下海底线无法自动准确检测和提取,造成斜距改正后目标图像严重畸变和错位问题,基于侧扫声呐成像机理以及图像特点,提出了海底线最后峰值检测法和基于海底变化渐进性和海底线对称性的海底线修复方法,结合Kalman滤波以及上述方法的特点和适用对象,给出了一种海底线自适应综合检测和提取方法以及完整的数据处理流程。该方法在烟台水域得到了应用,消除了海况差、悬浮物遮挡等问题的影响,实现了复杂海洋噪声影响下海底线的自动跟踪。与外部测深数据比较,取得了均方根为±0.17m的跟踪精度。
In view of the existing methods, the submarine line can not be accurately detected and extracted automatically when the image of the water column area of the side-scan sonar area is disturbed by the emission pulse, the sea echo, the wake and a large area of suspended solids, which causes serious distortion and misalignment of the target image after the slant correction Based on the imaging mechanism of the side-scan sonar and the characteristics of the image, the final peak detection method of submarine line and the submarine line restoration method based on submarine variation asymptotic and submarine line symmetry are proposed. Combined with Kalman filtering and the characteristics and applicable objects of the above method, A submarine line adaptive integrated detection and extraction methods and a complete data processing flow. The method has been applied in Yantai waters, eliminating the influence of poor sea conditions and suspended solids, and has realized the automatic tracking of the seafloor line under the influence of complex ocean noise. Compared with the external sounding data, the tracking accuracy of ± 0.17m was obtained.