【作者】 肖厚；

【导师】 陈世友；

【作者基本信息】 中国舰船研究院 ， 计算机软件与理论， 2011， 硕士

【摘要】 数据融合系统的性能通常受到传感器特性、环境和目标特性、融合模型、融合过程等多种因素影响。传感器、环境和目标特性的动态变化使得融合过程、融合模型、融合参数固定不变的数据融合系统难以取得较为理想的结果。提高数据融合系统的自适应性、减弱外界因素对融合系统性能的影响,是数据融合技术的重要研究内容。论文围绕数据融合系统自适应能力提升开展研究工作,主要包括:进行了航迹关联不确定度评定技术研究。基于信息不确定性度量理论,明确了航迹关联不确定度的概念;参考测量不确定度评定方法,对航迹关联不确定度评定方法进行了改进,使得评定方法更易理解、更加简单。提出并实现了一种自适应航迹数据相关方法。传统的航迹序贯相关方法中,序贯长度通常为设定的固定值。论文基于航迹关联不确定度评定结果,在线调整航迹相关方法的序贯长度,使得航迹相关判定的及时性与可靠性相统一,提升航迹序贯相关方法对传感器精度、目标分布及航路的适应性。提出并实现了基于数据驱动的系统误差估计方法。针对传统的传感器系统误差估计方法存在较大残余误差的问题,采用迭代学习方法,利用协作目标的高精度定位信息,建立传感器系统误差数值模型。进行了自适应数据融合系统的系统结构、处理流程和软件设计、实现与仿真实验。实验结果表明,航迹相关方法的序贯长度能够根据目标分布、航路以及航迹精度自动调整,能够及时输出可靠的判决结果;传感器系统误差经校准后,残余系统误差较小;数据融合系统对传感器特性和目标特性的变化具有一定的自适应。更多还原

【Abstract】 The overall performance of data fusion systems is affected by the nature of the sensors, the operational environment and the targets, the adopted fusion models, process, and so on. The dynamic changes of the nature of the sensors, the operational environment and the targets lead to that the data fusion systems with changeless fusion models, fusion process and fusion parameter wouldn’t get perfect results. Enhancing the adaptability of data fusion systems and weakening the effect of outside factors on the performances of fusion system is a hot research problem. This thesis thus focuses on the improvement in the adaptability of data fusion system. The idiographic research is as follows:The evaluation of the track correlation uncertainty is researched. The concept of the uncertainty of track correlation is defined based on the uncertainty theory. The evaluation method for track correlation uncertainty is revised based on the measurement uncertainty. The revised method can be comprehended and implemented more easily.An adaptive method for data correlation is presented and implemented. The length of sequence disposal usually is set changelessly. With the evaluating of track correlation uncertainty, the length of sequence is made to be self- adjustable, which makes the decicision of the data correlation more timely and more reliable, and so improved the adaptability of data correlation considering the different sensor accuracy, target distribution and routes.A sensor bias estimation method is presented and implemented with the base of data driven control theory. The traditional estimation methods often have large residual errors. Based on iterative learning approach, a data model of bias estimation is implemented with the use of the high precision positioning information of the collaborative targets.The architecture and process model of an adaptive data fusion system is designed, the corresponding software is developed and the simulation experiments is made. The experiment results show that the data correlation can adjust the length of sequence disposal according to the sensor accuracy, the target distribution and routes, the bias estimation method can acquire less residual bias and the data fusion system thus achives the capability in adapting the change of the nature of sensors and targets.更多还原