摘要
回顾了近年来国内外关于信息融合功能模型结构的研究现状,针对水下目标融合识别系统重点分析了具有数据、特征和决策3个融合层次的目标融合识别模型,给出了各融合层次几种常用的典型算法,即基于概率理论、数据分类理论以及人工智能理论的算法,分析了各种算法的优缺点和应用约束。最后对水下基于多传感器的目标融合识别系统的发展动向、存在的问题和解决这些问题的思路进行了展望。
Information fusion techniques, which can help to effectively reduce or eliminate the measuring uncertainty of distributed sensors＇ signal and fuse more comprehensive original vessel radiated signals, have been widely used in vari- ous military and civilian fields, and have attracted more concerns in the world. In this paper, the existing most accepted function models of the fusion systems are summarized, and a three-level （data-feature-decision） underwater automatic target recognition （ATR） system model is proposed. Subsequently, several commonly used fusion algorithms based on the probability theory, the data classification theory, and the artificial intelligence theory are presented, and their advan- tages, disadvantages and application constraints are analyzed. Moreover, the development trend of the underwater target fusion recognition system based on multi-sensor system, the existing problems, and the solutions to these problems are all discussed.
出处
《鱼雷技术》
2013年第3期234-240,共7页
Torpedo Technology
关键词
目标识别
信息融合
多传感器系统
融合算法
target recognition
information fusion
multi-sensor system
fusion algorithm
