本文为美国MIT（作者：Gregory Thomas Nannig）的硕士论文，共70页。

自主导航验证是导航中的一项重要功能。目前的技术水平是手动绘制雷达距离或视觉方位线到地标，这些地标在使用的传感器和海图上都是可分辨的，但需要训练有素的人员。在自动导航中，这个问题可以通过使用一个向外观察的传感器（如激光雷达或普通雷达）的同时定位绘图（SLAM）过程来解决。SLAM系统的输入之一是某种形式的里程计。

本论文研究在海洋环境中，以单一雷达感测器为基础实现实时里程表与定位。该雷达广泛应用于船舶上，可以作为一种非侵入式的实时里程测量系统来实现。与其他里程计方法不同，如多普勒计程仪等，这种雷达处理方法能够估计海流和海风对船只运动的影响。为了尽量减小雷达噪声和船舶转动的影响，采用了不同的算法配置。最后的方法能够在船只上实时运行，在内陆水域累积的误差约为1.5%。这个演示是在非实时进行的真实世界的数据收集，然后再输入到求解器中顺序求解。

Independent navigation verification is animportant function in navigation. The current state of the art is to manuallyplot radar ranges or visual lines of bearing to landmarks that aredistinguishable both on the sensor being used and on the chartthis requireshighly trained personnel. In automated navigation this problem can be solvedwith a Simultaneous Localization and Mapping (SLAM) process using anoutward-looking sensor, like a LIDAR or a RADAR. One of the inputs for a SLAMsystem is some form of odometry. This thesis looks at implementing real-timeodometry and positioning in a marine environment, based on a single radarsensor. The radar used is widely available on ships, and this system could beimplemented as a non-intrusive, real-time odometry measurement. Unlike othermethods for odometry, like dopper logs, dead reakoning, or shaft logs, thisradar method is able to estimate the impact of current and wind on the vessel'smovement. Different configurations of the algorithm were used to try andminimize the impact of radar noise and vehicle rotations. The final method isable to run in real-time on a vehicle and accumulates about 1.5% error,at-least in inland waters. This demonstration was conducted offvehicle onreal-world data that was collected and then fed into the solver sequentially.

1.  引言

2. 项目背景

3. 理论背景

4. 实验方法

5. 结果

6. 结论

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