摘要
为提高动力定位的精度,装备有动力定位系统的船舶通常会配备多个相同和不同类型的传感器对其状态进行测量.针对采用不同类型传感器的场合,提出了一种改进自适应加权融合算法.该算法可以更准确地计算各个传感器的方差,提高数据融合的精度.另外,针对采用相同类型传感器的场合,提出了一种改进权值动态分配算法.利用迭代方法解决了权值动态分配法需要保存历史数据的问题,提高了算法的实时性.仿真结果表明,在传感器类型不同时,改进自适应加权融合算法的精度明显高于传统自适应加权融合算法;在传感器类型相同时,改进权值动态分配算法的精度和实时性均高于传统自适应加权融合算法和改进自适应加权融合算法.
In order to improve the accuracy of dynamic positioning, the ship equipped with a dynamic positioning system is usually equipped with several sensors with same and different types to measure its status. An improved adaptive weighted fusion algorithm is proposed for the occasion of different types of sensors. The algorithm can accurately calculate the variance of each sensor and improve the accuracy of data fusion. In addition, an improved weighted dynamic allocation algorithm is proposed for the occasion of the same types of sensors. The problem that the weighted dynamic allocation algo- rithm needs to preserve the historical data is solved by using the iterative method, which improves the real-time performance of the algorithm. The simulation results show that the accuracy of adaptive weighted fusion algorithm is significantly higher than that of the traditional adaptive weighted fusion algorithm when the types of sensors are different, and the accuracy and real-time performance of the improved weight dynamic allocation algorithm are higher than those of the traditional adaptive weigh- ted fusion algorithm and the improved adaptive weighted fusion algorithm when the types of sensors are the same.
出处
《武汉理工大学学报（交通科学与工程版）》
2016年第4期663-669,共7页
Journal of Wuhan University of Technology（Transportation Science & Engineering）
基金
国家自然科学基金项目资助(61301279
51479158)
关键词
动力定位
数据融合
自适应加权融合
权值动态分配
dynamic positioning
data fusion
adaptive weighted fusion
dynamic allocation of weigh- ting factors
