摘要
船舶轴频电场是一种具有明显目标特征的极低频信号,对船舶的水下非声探测具有重要作用。对船舶轴频电场信号小波模极大值的尺度变化进行分析,根据目标信号和噪声的差异,采用Hermite插值对目标信号小波模极大值进行快速重构;提取目标特征频率范围内的能量均值为特征值,采用滑动检测方法对目标进行检测。实测和仿真数据对该算法的验证结果表明,此方法相对小波包熵检测算法的检测效果较好,虚警率较低,当SNR为-5.9 dB时检测率相对提高50%左右,并且在SNR为-8.2 dB时仍然具有86%的检测率。
The ship’s shaft-rate（SR） electric field propagating in seawater at extremely low frequency,plays an important role in the non-acoustic detection.The different characteristic of wavelet modulus maximum along with the scale is analyzed in the lab.Then the de-noising algorithm based on wavelet modulus maximum is introduced in the signal processing.With the Hermite interpolation being applied in the signal reconstructing process from wavelet transform maxima,the practicability of this algorithm is ensured consequently.Finally,the mean energy at characteristic frequency is selected as characteristic value to detect the target by sliding power spectrum algorithm.The effectiveness of the detection algorithm is verified both using measured data and simulated data.The verified result shows that the detection algorithm provides a better detecting performance and lower false alarm probability compared with the algorithm based on wavelet packet entropy.The detecting probability of this algorithm enhances about 50% when the signal-to-noise ration（SNR） is-5.9 dB,and it can keep 86% when the SNR is-8.2 dB.
出处
《兵工学报》
EI
CAS
CSCD
北大核心
2013年第5期579-584,共6页
Acta Armamentarii
基金
国家自然科学基金项目(51109215)
关键词
信息处理技术
船舶
电场
轴频
小波变换
信号检测
算法
information processing
ship
electric field
shaft-rate
wavelet transform
signal detection
algorithm
