【作者】 王停停；

【导师】 韩新洁；

【作者基本信息】 大连海事大学 ， 检测技术与自动化装置， 2012， 硕士

【摘要】 随着航运业的蓬勃发展,海上运输船舶数量不断增加,交通日益繁忙,船舶碰撞事故时有发生。因此,避碰问题就成为当前学者重要的研究对象。而解决避碰问题关键是要明确得知目标船的具体信息,从而辅助船员进行避碰操作。本文研究船舶航海仪器中的导航设备：AIS(Automatic Identification system)和雷达。它们各自都存在优缺点,不能单独作为船舶航行的唯一安全监测手段。多传感器信息融合技术是一个在多级别上对各个传感器的观测数据进行综合处理的过程,是多学科、多部门、多领域所共同关心的高层次共性关键技术,包括中国在内的很多国家都把它列为下一阶段重点发展的关键技术。本文以多传感器信息融合技术为基础,对AIS与雷达动态信息融合算法做了较为深入的研究。首先,读入AIS与雷达数据,经过坐标转换后将二者的信息统一在平面直角坐标系下。以AIS的航迹信息为中心,根据时间距离粗关联准则,将不满足粗关联准则的雷达航迹信息排除。其次,将AIS与雷达信息进行时间校准,使其同步,便于航迹关联与航迹融合。然后,采用多因素模糊综合决策航迹关联算法,对满足粗关联的雷达信息与AIS进行航迹关联判断,根据模糊综合隶属度判断出与AIS航迹信息满足固定关联的一条雷达信息。最后,对满足固定关联的AIS与雷达航迹信息,采用改进的自适应航迹加权融合算法进行航迹融合处理。为提高融合精度,采用卡尔曼滤波算法,在融合之前分别对AIS和雷达信息进行跟踪与滤波处理。仿真和测试结果表明：论文采用的多因素模糊综合决策航迹关联算法可以准确的判断AIS和雷达航迹是否来自同一目标船。在最小均方误差条件下,经自适应加权航迹融合算法融合后的航迹更接近运动目标的真实航迹,大大提高了目标信息的准确性。更多还原

【Abstract】 With the development of the shipping industry, the number of ships continues to increasing and resulting in ship collisions at last. Therefore, avoiding the collision of the ships becomes an important object of the current scholars. The most important thing to solve the collision is to clearly indicate the specific target information of the ship. The paper is introduced AIS system and radar. Because of their respective advantages and disadvantages, each of them is not used alone as the only safe means of monitoring the voyage. Multi-sensor information fusion technology can greatly improve the accuracy of target information. This technology has become a very active research field. Many countries, including China, regard it as key technologies on the next phase.Based on multi-sensor information fusion technology, the paper is studied deeply on dynamic information fusion algorithm of AIS and radar.Firstly, the paper is studied on getting the data of AIS and radar, and finishing the coordinate transformation, and then deleting the track of radar which does not meet the guidelines of the crude association. Secondly, the paper is studied on making it easy to finish track association and track fusion by putting the information of AIS and radar on the same time. Thirdly, the paper is used multi-factor fuzzy decision-making track correlation algorithm to make judgment of the track association of radar and AIS which is meeting the rule of track associate. Finally, it is to make the track of AIS associated with the track of radar. In order to improve the integration accuracy, the paper finally is discussed the Kalman filter algorithm to make tracking and filtering of the AIS and radar information before fusion.The results of simulation and test show that:the multi-factor fuzzy integrated decision-making track correlation algorithm is accurate. In the minimum mean square error conditions, the adaptive weighted track fusion algorithm is effective and accurate.更多还原