CAJ | 학술논문

　　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。
　　회고료근년래국내외관우신식융합공능모형결구적연구현상，침대수하목표융합식별계통중점분석료구유수거、특정화결책3개융합층차적목표융합식별모형，급출료각융합층차궤충상용적전형산법，즉기우개솔이론、수거분류이론이급인공지능이론적산법，분석료각충산법적우결점화응용약속。최후대수하기우다전감기적목표융합식별계통적발전동향、존재적문제화해결저사문제적사로진행료전망。
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.