The Study Of Proton Magnetometer FID Signal Processing Algorithm

Proton magnetometer is the equipment for the observation and acquisition of the magnetic field and its abnormal data, which uses the lannor precession effect of static excitation proton to measure magnetic fields.The FID signal of proton magnetometer probe, a relatively low signal-to-noise ratio, is attenuating as an exponential with time. So, the low signal-to-noise ratio and high-precision frequency measurement techniques plays an important role in improving the measurement precision, especially the accuracy.Thus, the algorithm of precision frequency measurement is a hot today.The paper focuses on the FID signal characteristics and frequency measurement method of proton magnetometer, mainly to the study of FID signal processing based on some algorithms, such as FFT, autocorrelation, wavelet, adaptive, Chaos,FDM, SVD, Prony method and so on. First, it briefly introduces the theory of these algorithms, the analysis of applicability of FID signal, and then achieves FID signal processing based on these algorithms and gives simulation results. Finally, the contrast of improvement of frequency measurement is analyed and simulated to prove the effectiveness and consistency of the algorithm. In addition, the paper also studies the principle and structure of a proton magnetometer, the relationship between FID signal-to-noise ratio and frequency measurement accuracy, and the suppression of FID signal interference.The first chapter of the paper introduces the purpose, the significance, domestic and foreign research background, then points out the current problems, finally concludes the research content and the key technology which will be solved;The proton magnetometer principle and structure is nesscery for studying proton magnetometer FID signal.Therefore, the second chapter of the paper briefly describes the structure of instrument, and discusses the overall block diagram of the the FID signal frequency measurement,which gives the foundation for the subsequent part of the study design;The third chapter studies the FID signal characteristics:analyzing the FID signal noise background, the signal characteristics, and discussing the direct frequency measurement and indirect frequency measurement method, then studying frequency conversion. Finally, this chapter mainly studies FID signal-to-noise ratio and the measured frequency accuracy relationship, through theoretical analysis, tryto get the expression of the relationship in order to provide a guarantee for later study;The chapter IV achieves the FID signal processing based on the conventional algorithms. It mainly studies FFT algorithm, Chaos algorithm, Auto-correlation algorithm, relevant adaptive algorithm and wavelet adaptive algorithm. After analyzing the basic principles and applicability of the FID signal, the FID signal based on these algorithms are processed respectively. Besides, depending on the signal-to-noise ratio of the FID signal, some simulation experiments are done and the experimental results are given to show the improvement of frequency measurement and the effectiveness and consistency of the algorithm;The fifth chapter studies the FID signal processing of proton magnetometer based on FDM algorithm. According to the FID signal characteristics and needs of the FDM algorithm, the FID signal matrix mathematical modeling is founded. Using the Hilbert, Taylor transform to make a real signal into a complex signal, four points of the complex signal matrix is discussed.Then, the paper analyzes the basic theory of the FDM algorithm and the applicability of the FID signal, and the FID signal processing based on FDM is done. Finally, depending on the signal-to-noise ratio of the FID signal, some simulation experiments are done and the experimental results are given to show the improvement of frequency measurement and the effectiveness and consistency of the algorithm;The sixth chapter mainly studies the FID signal processing based on SVD algorithm. SVD is used to reduce signal noise, reconstruction phase space, singular value decomposition and inverse transform, in order to extract useful signal. Therefore, after analyzing the basic theory and applicability of the FID signal, this chapter processes FID signal based on SVD algorithm. So, depending on the signal-to-noise ratio of the FID signal, some simulation experiments are done and the experimental results are given to show the improvement of frequency measurement and the effectiveness and consistency of the algorithm;The seventh chapter mainly studies the FID signal processing based on Prony method. The paper analyzes the basic principles of the Prony method, the applicability of the FID signal, and then some improvements of method is got. Besides, depending on the signal-to-noise ratio of the FID signal, some simulation experiments are done and the experimental results are given to show the improvement of frequency measurement and the effectiveness and consistency of the algorithm;The last chapter summarizes the results, conclusions and major innovation of thesis. The shortcomings and suggestions for further research are pointed out.