基于无人艇载侧扫声呐的水下目标定位方法研究

水下目标高精度定位是无人艇开展海底测绘、航道清理、沉船打捞等任务的重要前提。 然而,现有的基线式定位方法无 法对未知水域内的目标进行精确定位。 实际任务中,无人艇往往需要搭载侧扫声呐并辅以其他手段来确定水下目标的准确位 置。 针对无人艇水下目标定位难题,首先对侧扫声呐水下目标定位过程进行建模,然后分析姿态误差对水下目标定位造成的影 响,利用姿态矫正矩阵消除姿态误差,最后利用离散卡尔曼滤波算法对多点测量数据进行最优估计,得到水下目标的精确位置。 仿真实验和无人艇集成实验结果表明,该定位方法能够有效的减小测量过程中的误差,平均定位精度达到 0. 334 m。

Research on underwater target location based on side-scan sonar carried by unmanned surface vehicle

High-precision positioning of underwater targets is an important prerequisite for unmanned surface vehicle (USV) to carry out tasks, such as seabed mapping, channel cleaning, and wreck salvage. However, the existing baseline positioning methods cannot accurately locate the targets in unknown waters. In practical tasks, USV needs to be equipped with side-scan sonar and supplemented by other means to determine the accurate position of underwater targets. In this article, aiming at the underwater target localization problem of the unmanned boat, we first model the underwater target localization process of side-scan sonar. Then, the influence of attitude error on underwater target positioning is analyzed, and the attitude error is eliminated by using an attitude correction matrix. Finally, the discrete Kalman filter algorithm is used to optimally estimate the multi-point measurement data and get the accurate position of the underwater target. The results of simulation experiments and USV integration tests show that the proposed method can effectively reduce the systematic errors in the measurement process and the average positioning accuracy reaches 0. 334 m