摘要
信号特征的有效提取是水声信号检测的前提,是水下声引信实现目标可靠探测的关键,如何在复杂、多变的水下环境中有效提取信号特征是声引信检测的难点。针对基于能量特征的水声信号检测方法的局限性,对水声信号信息熵特征提取方法展开研究,使用改进排列熵算法(Multiscale Improved Permutation Entropy,MIPE)提取了主动和被动声引信信号的熵特征,并分别使用扩展窗和滑动窗两种计算方法展开分析讨论。计算和分析结果表明,声引信信号的改进排列熵特征明显,可以有效区分目标信号和背景噪声,实现对目标的过靶检测。
Effective extraction of signal features is the prerequisite for underwater acoustic signal detection and the key to achieving reliable target detection in underwater acoustic fuzes.How to effectively extract signal features in complex and variable un⁃derwater environments is a main difficulty in acoustic fuze detection.Aiming at the limitations of underwater acoustic signal detec⁃tion methods based on energy features,the information entropy feature extraction method of underwater acoustic signals is studied.An improved permutation entropy algorithm is used to extract the entropy features of active and passive acoustic fuze signals using extended window and sliding window methods.The calculation and analysis results show that the improved permutation entropy fea⁃ture of acoustic fuze signals is obvious,which can effectively distinguish target signals and background noise,and achieve target de⁃tection.
作者
顾云涛
曹浩
张俊
GU Yuntao;CAO Hao;ZHANG Jun(Xi'an Bureau of Naval Equipment Department,Xi'an 710068;No.705 Research Institute of China State Shipbuilding Corporation Limited,Xi'an 710075)
出处
《舰船电子工程》
2023年第8期216-222,共7页
Ship Electronic Engineering
关键词
声引信
改进排列熵
熵特征
acoustic fuze
improved permutation entropy
entropy characteristics
