Noise characterization for the FID signal from proton precession magnetometer

Proton precession magnetometer is a high-precision device for weak magnetostatic field measurement. The measurement accuracy depends on the frequency measurement of free induction decay (FID) signal, while the signal to noise ratio (SNR) is an important factor affecting the results. Many signal processing methods have been proposed to improve the SNR of FID signal. However, the theoretical analysis of different types of noises for FID signal has not be conducted yet. In addition, the relationship between the frequency measurement accuracy and SNR has not been explicitly established and quantified. This paper first proposes a background noise model based on the extracted features from the FID signal. With this model, background noises, such as white noise, narrow-band noise, and phase noise etc., can be calculated and estimated. Secondly, the relationship between the frequency measurement accuracy and SNR is identified. We also built a prototype proton magnetometer for field tests and validation purpose. Experiments were conducted to investigate this relation through simulation. Different values for frequency accuracy were obtained with different SNRs from the acquired FID signals from field tests. The consistence between the measurement and computational results is observed. When SNR is larger than 30 dB, the absolute frequency accuracy becomes constant which is about 0.04 Hz. With the stability taken into account, the accuracy can be better even when the SNR is higher than 30 dB. This study provides a reference to optimize the design of proton precession magnetometer and the frequency calculation for FID signal.

[1]  Michal Ulvr,et al.  Precise Calibration Method for Triaxial Magnetometers Not Requiring Earth’s Field Compensation , 2015, IEEE Transactions on Instrumentation and Measurement.

[2]  S. Kiselev,et al.  Theodolite-borne vector Overhauser magnetometer: DIMOVER , 2006 .

[3]  Khachatryan,et al.  Performance of electron reconstruction and selection with the CMS detector in proton-proton collisions at √s=8 TeV , 2015 .

[4]  Nando de Freitas,et al.  An Introduction to Sequential Monte Carlo Methods , 2001, Sequential Monte Carlo Methods in Practice.

[5]  Huan Liu,et al.  A High-Precision Frequency Measurement Algorithm for FID Signal of Proton Magnetometer , 2016, IEEE Transactions on Instrumentation and Measurement.

[6]  P. Ivanov,et al.  Development of the read-out ASIC for muon chambers of the CBM experiment , 2015 .

[7]  James A. Slavin,et al.  Observations of Mercury's northern cusp region with MESSENGER's Magnetometer , 2011 .

[8]  Kiwoong Kim,et al.  Proton spin-echo magnetometer: a novel approach for magnetic field measurement in residual field gradient , 2015 .

[9]  Toshihiro Furukawa,et al.  Intensity estimation method of the FID signal based on the high-order Prony Method including evaluation used to the priori information in quantitative NMR , 2014, 2014 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT).

[10]  Reto Meuli,et al.  Accuracy and Precision of Head Motion Information in Multi-Channel Free Induction Decay Navigators for Magnetic Resonance Imaging , 2015, IEEE Transactions on Medical Imaging.

[11]  Shuang Zhang,et al.  Overhauser magnetometer sensor design for magnetic field observation , 2016, Optical Engineering + Applications.

[12]  Wang Hongliang,et al.  The Study of Matrix Mathematical Model Construction of PPM FID Signal Associate With FDM , 2012 .

[13]  Zhang Shuan Design of JPM-1 Proton Magnetometer Based on DSP , 2014 .

[14]  S. Tumanski,et al.  Modern magnetic field sensors – a review , 2013 .

[15]  A. Denisov,et al.  Broadband mode in proton-precession magnetometers with signal processing regression methods , 2014 .

[16]  Toshihiro Furukawa,et al.  Application of intensity estimation method of the FID signal based on the high-order Prony estimation Method and selective evaluation criterion to Purity Estimation in quantitative NMR, dependence of the 13C decoupling and the sample spinning , 2014, 2014 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS).

[17]  J. M. Morris,et al.  Noise reduction for NMR FID signals via Gabor expansion , 1997, IEEE Transactions on Biomedical Engineering.

[19]  Robert N. McDonough,et al.  Detection of signals in noise , 1971 .

[20]  Janusz Mroczka,et al.  Prony’s Method with Reduced Sampling - Numerical Aspects , 2014 .

[21]  C. Park,et al.  Estimation of hydrothermal deposits location from magnetization distribution and magnetic properties in the North Fiji Basin , 2013 .

[22]  Huan Liu,et al.  Research on a secondary tuning algorithm based on SVD & STFT for FID signal , 2016 .