摘要
针对随着传播距离的增大极低频电场衰减很快,很容易被环境噪声所掩盖,提出了基于谐波小波的自适应谱线增强器来提高微弱轴频电场远程检测能力的算法。根据实际情况和仿真信号的特点,谐波小波对信号进行9层分解。利用该算法对舰船电磁场缩比模型产生的轴频电场的实测数据进行处理,结果表明该算法能够实时有效地将微弱的轴频电场特征信号从环境背景噪声中分离出来,大大提高了舰船轴频电场的检测能力。同时采用基于基于谐波小波算法的自适应谱线增强的自适应迭代次数比采用最小均方算法的自适应迭代次数少,说明采用基于谐波小波算法的自适应谱线增强能快速收敛。
With the rapid attenuation of extremely low frequency field due to the increasing transmis- sion distance, the field is readily covered by environmental noises. In view of this, an algorithm was then advanced to improve the capability of remotely detecting the extremely low frequency （ELF） field by virtue of the harmonic-wavelet adaptive line enhancer. This algorithm was used to process the actu- al measured data of the shaft-rate modulated electric field produced by use of vessel＇ s physical scale models, whose results demonstrate that the algorithm effectively separated the weak characteristic signals of shaft-rate modulated electric field from the environmental noises at real time, greatly improving the capability of detecting a vessel＇ s shaft-rate modulated electric field. In view of the facts and the char- acteristics of simulated signals, harmonic wavelets were used to decompose the signals into 9 layers. In the meanwhile, there were less adaptive iterations due to the adaptive line enhancement obtained by the harmonic wavelet algorithm than by the least mean square algorithm. This indicates that the adaptive line enhancement based on the harmonic wavelet algorithm is able to converge at higher rate.
出处
《电机与控制学报》
EI
CSCD
北大核心
2013年第10期77-84,共8页
Electric Machines and Control
基金
山东省高等学校科技计划项目(J12LN37)
泰山学者海外特聘专家项目(C2010-T005)
山东省自然科学基金项目(ZR2013FM014)
关键词
轴频电场
小波
谐波小波
自适应
谱线增强
shaft-rate electric field
wavelet
harmonic wavelet
adaptive
line enhancement
