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兵工学报 ›› 2013, Vol. 34 ›› Issue (5): 579-584.doi: 10.3969/j.issn.1000-1093.2013.05.011

• 研究论文 • 上一篇    下一篇

基于小波模极大值的船舶轴频电场检测算法研究

贾亦卓, 姜润翔, 龚沈光   

  1. 海军工程大学兵器工程系, 湖北武汉430033
  • 上线日期:2013-07-22
  • 作者简介:贾亦卓(1985—),博士研究生
  • 基金资助:

    国家自然科学基金项目(51109215)

Research on Wavelet Modulus Maximum-based Detection Algorithm of Ship爷s Shaft-rate Electric Field

JIA Yi-zhuo, JIANG Run-xiang, GONG Shen-guang   

  1. Department of Weaponry Engineering, Naval University of Engineering, Wuhan 430033, Hubei, China
  • Online:2013-07-22

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。

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

Abstract:

The ship爷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 max- imum 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 sig- nal 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 veri- fied 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.

Key words: information processing, ship, electric field, shaft-rate, wavelet transform, signal detection, algorithm

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