一种基于多波束测深仪的水下同步定位与地图构建方法

数据库辅助导航系统（DBRNS）可以校正惯性导航系统（INS）的累积误差，是自主水下潜航器的重要辅助导航手段，但DBRNS的有效运行依赖于高分辨率的基准图。为解决这一问题，提出一种基于多波束测深仪的图优化同步定位与地图构建（SLAM）方法。该方法在通用图优化SLAM方法的前端部分增加误匹配检测模块，减少了错误闭环对结果造成的不良影响。此外，新方法将局部灰度值编码算法用于闭环检测模块以提高闭环检测的精度。基于真实海底地形图的仿真实验结果表明，相对于通用图优化SLAM方法，采用新方法对INS轨迹进行校正可以取得更高的定位精度。

A Multi-beam Sonar-based Graph SLAM Method

Database-referenced navigation systems(DBRNSs) are commonly used in autonomous underwater vehicles as underwater auxiliary navigation systems to correct the cumulative errors of inertial navigation systems. However, the DBRNS cannot run if a high resolution database cannot be obtained. A multi-beam sonar-based graph simultaneous localization and mapping (SLAM) method is proposed. A mismatch detection module is added to the front end to reduce the negative impact caused by the false closed-loop detection results. In the proposed method, the local gray value coding algorithm is used for the closed-loop detection module in order to improve the detection accuracy. Simulations based on the actual seabed terrain base map show that, compared with the general graph SLAM method, the proposed method can achieve higher positioning accuracy. Key