摘要
当前舰船辐射噪声识别方法存在识别率低,对环境鲁棒性差等缺陷,为了对复杂环境下的舰船辐射噪声识别进行准确识别,提出了BP神经网络的舰船辐射噪声识别方法。首先采集舰船辐射噪声,并提取舰船辐射噪声识别有效特征参数,然后采用BP神经网络建立舰船辐射噪声识别模型,从而实现对舰船辐射噪声信号的分类和识别,最后进行舰船辐射噪声识别的仿真测试。结果表明,相对于已有的舰船辐射噪声识别方法,BP神经网络提高了舰船辐射噪声识别率,可以对各种舰船辐射噪声信号进行准确分类。
At present,the recognition method of ship radiated noise has some shortcomings,such as low recognition rate and poor robustness to environment.In order to recognize ship radiated noise accurately in complex environment,a recognition method of ship radiated noise based on BP neural network is proposed.Firstly,the ship radiated noise is collected,and the effective characteristic parameters of ship radiated noise recognition are extracted.Then,the model of ship radiated noise recognition is established by using BP neural network,so as to realize the classification and recognition of ship radiated noise signals.Finally,the simulation test of ship radiated noise recognition is carried out.The results show that,compared with the existing methods of ship radiated noise recognition,BP neural network improves the recognition rate of ship radiated noise,and can accurately classify all kinds of ship radiated noise signals.
作者
李倩
LI Qian(Tangshan Vocational and Technical College,Tangshan 063300,China)
出处
《舰船科学技术》
北大核心
2019年第24期22-24,共3页
Ship Science and Technology
关键词
BP神经网络
舰船辐射
噪声识别
仿真测试
BP neural network
ship radiation
noise recognition
simulation test
