基于深度学习的直升机旋翼声信号检测与识别一体化算法  

An Integrated Algorithm for Helicopter Rotor Sound Signal Detection and Recognition Based on Deep Learning

作　　者：郭磊 林啸宇 王勇[3] 陈正武[3] 常伟 GUO Lei;LIN Xiaoyu;WANG Yong;CHEN Zhengwu;CHANG Wei(School of Computer Science and Engineering,University of Electronic Science and Technology of China,Chengdu 611731;School of Information and Software Engineering,University of Electronic Science and Technology of China,Chengdu 610054;China Aerodynamics Research and Development Center,Mianyang Sichuan 621010)

机构地区：[1]电子科技大学计算机科学与工程学院,成都611731 [2]电子科技大学信息与软件工程学院,成都610054 [3]中国空气动力研究与发展中心,四川绵阳621010

出　　处：《电子科技大学学报》2023年第6期925-931,共7页Journal of University of Electronic Science and Technology of China

摘　　要：基于直升机旋翼声信号的目标检测与识别是低空目标预警领域的一个重要问题。目前的相关研究将检测和识别分别进行研究,而在实际应用中检测与识别是一个整体过程。针对上述问题,提出了一种基于深度学习的直升机旋翼声信号检测与识别一体化算法。算法首先通过融合特征提取和支撑向量机进行目标检测,再将检测到的潜在直升机声目标的信号段基于深度学习进行分类识别。通过实验数据测试了该算法的效果,实验结果表明,该算法使检测率、识别率均得到较大幅度的提升,增强了检测识别精准度。The detection and recognition of helicopter rotor acoustic signals are the important problems in the field of low altitude target warning.The current algorithms treated detection and recognition separately,but in practical applications,detection and recognition is a whole process.In order to solve the above problems,this paper proposes an integrated detection and recognition algorithm for helicopter rotor acoustic signal based on deep learning.Firstly,the target is detected by fusing feature extraction and support vector machine,and then the signal segments of potential helicopter acoustic targets are classified and recognized based on deep learning.The effect of the algorithm is studied and tested in detail by constructing experimental data.Experimental results show that the detection rate and recognition rate of the algorithm are greatly improved,and the detection accuracy and recognition accuracy are greatly enhanced.The algorithm has high research and application values.

关 键 词：声目标识别 深度学习 特征提取 直升机旋翼声信号 信号处理 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]