自适应LMS和相关算法在GMI磁传感器信号检测中的应用
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优秀研究生创新资助项目(B110302);湖南省研究生科研创新项目(CX2011B013)


Application of adaptive LMS algorithm and correlation in  signal detection for GMI magnetic sensor
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    摘要:

    在GMI磁传感器的研制中,微弱磁场信号经常淹没于电路固有噪声中。当非晶丝GMI(Giant Magneto-Impedance)磁传感器的输出信噪比小于0dB时,常规的峰值检波方法无法检出传感器信号。针对此问题,提出了一种新的微弱信号(信噪比小于0dB)检测方法,利用LMS自适应滤波算法提取非晶丝GMI磁传感器输出信号的特征参数,将该特征参数与理想参数进行相关运算,并根据相关值的大小来确定信号大小,从而实现对微弱磁信号的测量。仿真结果表明,采用LMS自适应滤波算法和相关分析相结合的方法,对于传感器输出信噪比等于-10dB的微弱信号,根据相关值与外磁场大小的对应关系,仍然可以确定外磁场大小。

    Abstract:

    In the development of GMI magnetic sensor, weak magnetic signals are always submerged in the circuit intrinsic noise. Since traditional peak detecting method is impossible to detect GMI sensor’s output when its SNR is lower than 0dB,a new method is presented to detect the GMI probe’s weak signals(SNR<0dB). The LMS algorithm was applied firstly to extract the characteristic parameters of the weak signals, and then the cross-correlation function between the characteristic parameters and the idea ones was calculated. Finally the maximal correlation values were regarded as weak signals to be detected by means of calibration. The simulating results indicate that this method can not only detect but also measure the magnetic field by the corresponding relationship of magnetic field intensity and the maximal correlation values, even the SNR of GMI magnetic sensor’s output is 10dB.

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潘仲明,丁浩,陈敏.自适应LMS和相关算法在GMI磁传感器信号检测中的应用[J].国防科技大学学报,2013,35(1):142-146.
PAN Zhongming, DING Hao, Chen Min. Application of adaptive LMS algorithm and correlation in  signal detection for GMI magnetic sensor[J]. Journal of National University of Defense Technology,2013,35(1):142-146.

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  • 收稿日期:2012-05-28
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  • 在线发布日期: 2013-03-13
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