摘 要：水声信号辨识技术是实现水下武器装备智能化的关键技术之一。由于极其复杂的水下背景环境，水声信号辨识技术发展缓慢。为探索研究新型水声信号辨识技术，本文提出基于脑认知信号的水声信号辨识方法。从大脑认知出发，获取水声目标信号辨识时的脑认知信号，通过范式设计，构建水声目标与脑认知信号的相关模型，并验证脑认知信号用于水声信号辨识的可行性。
关键词：脑认知信号；水声信号；智能辨识；响应特征
中图分类号：TN911.7 文献标识码：A 文章编号：2096-4706（2019）04-0032-03
Research on Intelligent Identification of Underwater Acoustic Signals Based on
Brain Cognitive Signals
YUAN Daoren，CAI Yubao，HU Zhengzheng，MA Liuyang
（The 27th Research Institute of China Electronic Science and Technology Group Corporation，Zhengzhou 450047，China）
Abstract：Identification of underwater acoustic signal is one of key techniques to realize the intelligent submarine weapon. However，this technique develops slowly due to the extremely complex submarine environment. In order to explore a new underwater acoustic signal identification technology，this paper proposes an underwater acoustic signal identification method based on brain cognitive signals. Starting from brain recognition，the brain cognitive signals are acquired when underwater acoustic target signals are identified.
Through the paradigm design，the correlation model between underwater acoustic target and brain cognitive signals is constructed，and the feasibility of using brain cognitive signals for underwater acoustic signal identification is verified.
Keywords：brain cognitive signals；underwater acoustic signals；intelligent identification；response characteristics
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作者简介：袁道任（1987.10-），男，汉族，河南郑州人，硕士研究生，研究方向：生物电子信息，模式识别等。