CAJ | 학술논문

为了有效地从海洋环境电场背景中检测微弱的船舶轴频电场信号，对轴频信号小波模极大值的尺度分布特性进行了分析，在得出轴频观测信号中噪声模极大值的幅度和分布稠度均随尺度增大而减小的结论的基础上，通过提取最大分解尺度的模极大值能量作为特征值，利用滑动检测方法对目标进行检测，并且避免了小波模极大值的重构过程，因而计算量小，检测速度较快．最后，分别使用实测数据和仿真数据对该算法进行了验证，结果表明此算法在低信噪比情况下具有较好的检测效果，当SNR为-10．8dB时仍然具有79％的检测率．
위료유효지종해양배경전장배경중검측미약적선박축빈전장신호，대축빈신호소파모겁대치적척도분포특성진행료분석，재득출축빈관측신호중조성모겁대치적폭도화분포주도균수척도증대이감소적결론적기출상，통과제취최대분해척도적모겁대치능량작위특정치，이용활동검측방법대목표진행검측，병차피면료소파모겁대치적중구과정，인이계산량소，검측속도교쾌．최후，분별사용실측수거화방진수거대해산법진행료험증，결과표명차산법재저신조비정황하구유교호적검측효과，당SNR위-10．8dB시잉연구유79％적검측솔．
In order to effectively detect ship shaft-rate(SR) electric signal ,the wavelet modulus maximum’s scale-distribu-tion characteristics of the measured SR electric signal is analyzed .Based on the analysis result that the intensity and distribution den-sity of noise’s wavelet modulus maximum decreases along the scale ,a detecting algorithm was proposed to extract the modulus maximum power in the highest scale as feature value to detect the target glidingly .As the wavelet reconstruction is avoided in the de-noising process using wavelet modulus ,the detecting algorithm proposed can be easily achieved by hardware .In the end ,the ef-fectiveness of the proposed method is verified both using measured data and simulated data ,and simultaneity compared with the de-tecting algorithm based on wavelet packet entropy .The verified result shows that the detecting algorithm provides a better detecting performance ,and it can keep detection rate of 79% when the SNR is -10 .8dB .