肖元弼, 彭认灿, 暴景阳, 董箭, 吕程. 利用卡尔曼滤波改正多波束数据声速整体误差[J]. 武汉大学学报 ( 信息科学版), 2020, 45(9): 1461-1468. DOI: 10.13203/j.whugis20180261
引用本文: 肖元弼, 彭认灿, 暴景阳, 董箭, 吕程. 利用卡尔曼滤波改正多波束数据声速整体误差[J]. 武汉大学学报 ( 信息科学版), 2020, 45(9): 1461-1468. DOI: 10.13203/j.whugis20180261
XIAO Yuanbi, PENG Rencan, BAO Jingyang, DONG Jian, LÜ Cheng. Sounding Velocity Intergrated Error Correction Method of Multi-beam Data Based on Kalman Filtering[J]. Geomatics and Information Science of Wuhan University, 2020, 45(9): 1461-1468. DOI: 10.13203/j.whugis20180261
Citation: XIAO Yuanbi, PENG Rencan, BAO Jingyang, DONG Jian, LÜ Cheng. Sounding Velocity Intergrated Error Correction Method of Multi-beam Data Based on Kalman Filtering[J]. Geomatics and Information Science of Wuhan University, 2020, 45(9): 1461-1468. DOI: 10.13203/j.whugis20180261

利用卡尔曼滤波改正多波束数据声速整体误差

Sounding Velocity Intergrated Error Correction Method of Multi-beam Data Based on Kalman Filtering

  • 摘要: 针对传统多波束测深系统从误差源进行平差的后处理方式受声速误差等因素影响较大的应用局限, 提出了以相邻条带中央波束构建的每ping海底地形趋势线作为先验信息, 利用卡尔曼滤波(Kalman filter, KF)对声速整体误差影响下的测深数据系统性误差进行改正的方法。首先, 提取测深数据准确性相对较高的相邻条带的中央波束数据, 对多波束每ping测深点所在的区域海底地形构建大致走向的趋势线; 其次, 利用检测线中央波束与主测线交叉重叠部分的数据, 得到观测值的偏差和所构建海底地形趋势线的偏差; 最后, 结合得到的偏差, 以构建的趋势线作为先验信息对测深数据利用卡尔曼滤波进行改正, 并对改正后的数据进行精度分析与评估。实验表明, 对于声速整体误差引起的海底地形畸变, 利用卡尔曼滤波能够对边缘波束的系统性误差进行有效的改正。

     

    Abstract: Out the error source in tradition of multi-beam sounding system adjustment of post-processing methods are greatly influenced by factors such as sound velocity error limitation of application of adjacent strips the central beam is put forward to build each ping the topography of the trend line as a prior information, using Kalman filtering under the influence of the integrated error of sound sounding data of systemic error correction method. Firstly, the central beam data of adjacent bands with relatively high accuracy of the sounding data were extracted, and the trend line of the regional seabed topography of the area under which the multi-beam was located was constructed roughly. Secondly, the deviation of the observed value and the deviation of the trend line of the seabed topography are obtained by using the data of the overlaps between the central beam of the detection line and the main measuring line. Finally, based on the deviation obtained, the construction trend line is used as the prior information to correct the data using Kalman filtering, and the accuracy of the corrected data is analyzed and evaluated. The experimental results show that the system error of the edge beam can be corrected effectively by Kalman filter.

     

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