摘要
针对现有的磁异目标差值匹配检测算法在低信噪比下效果较差的问题,提出了一种基于相似性度量的匹配检测算法,通过构建衡量序列局部相似性的函数对实时磁异信号和背景场信号进行匹配处理,再利用小波包去噪进一步提高信噪比,最后将处理后的信号输入到OBF检测器中完成目标实时检测。研究结果表明在虚警率为0.42%下当输入信号信噪比为-9 dB时,该算法的检测率仍在90%左右,其在低信噪比下的检测效果明显优于差值匹配检测。
Aiming at the problem that the existing difference matching detection algorithm of magnetic anomaly targets has poor effect under low SNR, a matching detection algorithm based on similarity measure is proposed. The similarity function is used to match the real-time signal and the background field signal, then the wavelet packet denoising is used to further improve the SNR. Finally, the processed signal is input into the OBF detector to complete the real-time target detection. The research indicates that when the false alarm rate is 0.42%, and the SNR of the input signal is-9 dB, the detection rate of the algorithm is still around 90%, and its detection effect under low SNR is obviously better than that of difference matching detection.
作者
刘一飞
张宁
赵鹤达
徐磊
林朋飞
Liu Yifei;Zhang Ning;Zhao Heda;Xu Lei;Lin Pengfei(Academy of Weaponry Engineering,Naval University of Engineering,Wuhan 430033,China;Unit 91977 of PLA,Beijing 100000,China;Department of Hydropower and Chemical Defense,Dalian Naval Academy,Dalian 116000,China)
出处
《电子测量与仪器学报》
CSCD
北大核心
2022年第9期103-110,共8页
Journal of Electronic Measurement and Instrumentation
基金
军委科技委创新特区基金(20-163-00-TS-013-002-11)项目资助。
关键词
磁异信号
匹配检测
相似性度量
小波包去噪
正交基函数
magnetic anomaly signal
matching detection
similarity measure
wavelet packet de-noising
orthogonal basis functions
