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滤波与正交基分解在磁性目标检测中的应用
引用本文:杨勇,车振,石超.滤波与正交基分解在磁性目标检测中的应用[J].电子科技,2014,27(11):109-112.
作者姓名:杨勇  车振  石超
作者单位:(中国船舶重工集团公司第710研究所 磁学研究中心,湖北 宜昌 443003)
摘    要:通过对磁性目标磁异常信号时域和频域特性的分析可知,磁异常信号属于低频信号,且在实际磁异常探测中磁性目标信号被噪声淹没,信噪比较低。针对这种情况提出了基于低通滤波与正交基分解的检测方法,先分析数字滤波器特性,设计约束最小二乘FIR滤波器滤除高频噪声,再利用正交基分解检测算法,大幅提升了磁性目标信号的信噪比,从而实现了磁性目标检测。仿真试验表明,该方法可滤除高频噪声,提升信噪比,增强对磁性目标的检测能力

关 键 词:低频信号  磁异常探测  信噪比  约束最小二乘FIR滤波器  正交基分解  

Application of Low Pass Filter and Orthonormalized Functions Decomposition Algorithm in Magnetic Target Detection
YANG Yong , CHE Zhen , SHI Chao.Application of Low Pass Filter and Orthonormalized Functions Decomposition Algorithm in Magnetic Target Detection[J].Electronic Science and Technology,2014,27(11):109-112.
Authors:YANG Yong  CHE Zhen  SHI Chao
Affiliation:(Magnetic Research Center,No.710 R&D Institute,CSIC,Yichang 443003,China)
Abstract:Magnetic anomaly signal of magnetic target is low frequency signal by the analysis of time and frequency characteristic and SNR is low in magnetic anomaly detection. A new algorithm is proposed using FIR lowpass filter integrated into orthonormalized functions decomposition algorithm. Firstly constrained least square FIR filter is designed to filter the high frequency noise in the raw signal by the analysis of filter characteristic. Then the disposed signal is decomposed by orthonormalized functions decomposition algorithm to increase SNR. The simulation result demonstrates the method can filter the high frequency noise and increase the SNR to improve the detection ability of magnetic objects.
Keywords:low frequency signal  magnetic anomaly detection  SNR  constrained least square FIR filter  orthonormalized functions decomposition algorithm
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