【摘要】：與目前常用的基于磁通門(Fluxgate)、霍爾效應(yīng)(Hall)和磁電阻效應(yīng)等的磁傳感器相比較,基于巨磁阻抗效應(yīng)(Giant Magneto-Impedance,簡稱GMI)的GMI磁傳感器還具有靈敏度高、體積小、響應(yīng)速度快、磁滯小以及功耗低等優(yōu)點,在微弱磁場測量等領(lǐng)域具有廣闊的應(yīng)用前景。與此同時,以地球磁場為背景的磁異檢測(Magnetic Anomaly Detection,簡稱MAD)技術(shù),具有無源被動檢測、隱蔽性能好以及抗干擾能力強等特點,可廣泛應(yīng)用于資源勘探、交通運輸和軍事目標探測與跟蹤等領(lǐng)域。因此,開展GMI磁傳感器及磁異信號檢測技術(shù)方面的研究具有重要的理論意義和工程應(yīng)用價值。本文圍繞著GMI磁傳感器的設(shè)計以及鐵磁性目標所引起的磁異信號的檢測問題等內(nèi)容展開深入的研究,其主要包括:(1)簡要介紹了GMI效應(yīng)及其與驅(qū)動電流頻率之間的關(guān)系等內(nèi)容,研究了所選用非晶絲材料的頻率特性,并據(jù)此選取了敏感探頭的驅(qū)動電流頻率和線性工作區(qū)間;同時,利用直流線圈提供偏置磁場的方式,設(shè)計了一個差分式結(jié)構(gòu)的敏感探頭,提出了利用具有強噪聲抑制能力的正交鎖定差分電路代替峰值檢測電路作為GMI磁探頭的信號調(diào)理電路,并詳細分析了該信號調(diào)理電路的工作原理以及該GMI磁傳感器的各項性能;另外,根據(jù)第二代電流傳輸器(second generation Current Conveyor,簡稱CCII)和跨導運算放大器(Operational Trans-conductance Amplifier,簡稱OTA)等有源模塊的工作原理,利用現(xiàn)有商業(yè)芯片AD844,提出了一個振蕩條件和諧振頻率獨立可調(diào)節(jié)的雙輸出正交正弦振蕩器,并詳細介紹了該振蕩器的工作原理以及進行了非理想條件分析。(2)建立了磁異檢測的數(shù)學模型,詳細推導了基于三個正交基函數(shù)的磁異信號的表達式,并針對目標信號的特征時間已知的條件下,根據(jù)正交匹配濾波器組理論,提出并詳細闡述了適用于白噪聲情形下的基于正交基函數(shù)匹配濾波器組的磁異檢測系統(tǒng),并以此為基礎(chǔ),構(gòu)建并詳盡分析了可應(yīng)用于有色噪聲情形下的基于LMS自適應(yīng)AR模型的白化濾波器和正交基函數(shù)匹配濾波器組相結(jié)合的磁異檢測系統(tǒng)。同時,針對1/f分形噪聲為外界磁場環(huán)境和電路等噪聲的主要來源之一的情形,通過利用仿真驗證的方式,詳細分析了文中所設(shè)計的自適應(yīng)白化濾波器的預白化效果和磁異檢測系統(tǒng)的性能,同時利用實測數(shù)據(jù)進一步驗證了該檢測系統(tǒng)的可行性和優(yōu)越性。(3)以自回歸-滑動平均ARMA模型理論為基礎(chǔ),簡要介紹了可應(yīng)用于不平穩(wěn)時間序列情形下的求和自回歸-滑動平均(Auto-Regressive Integrated Moving Average,簡稱為ARIMA)模型及其建立流程,并針對磁異目標信號的特征時間未知且背景噪聲為非平穩(wěn)時間序列的情形,根據(jù)ARMA模型的L步預測公式,提出了基于ARIMA模型預測的磁異檢測算法,且利用實測數(shù)據(jù)和仿真分析相結(jié)合的手段,詳細分析了該檢測算法的性能并指出其存在的局限性。同時,以灰色關(guān)聯(lián)度理論為基礎(chǔ),進一步提出了基于ARIMA模型殘差與灰色關(guān)聯(lián)度相結(jié)合的磁異檢測算法,并通過仿真驗證的方式對其性能進行了詳細分析。(4)簡要介紹了離散小波變換與逆變換等理論,針對快速離散小波變換的分解過程中存在數(shù)據(jù)逐級減少等問題,引出了非抽樣離散小波變換的概念;利用小波變換具有時域-頻域空間局部化特性,根據(jù)小波閾值消噪的原理,通過分析傳統(tǒng)硬閾值法和軟閾值法中存在的不足之處,提出了基于加權(quán)模糊函數(shù)的小波閾值消噪的磁異檢測算法,并分別通過仿真驗證和實測數(shù)據(jù)分析的方式,詳細分析了該檢測算法的性能并指出該算法的優(yōu)越性;此外,利用小波變換對1/f噪聲具有預白化作用的特性,提出了基于非抽樣離散小波變換的小波系數(shù)能量的磁異檢測算法,不但詳細推導了該檢測算法的檢測概率、虛警概率等理論表達式,而且通過一系列仿真驗證實驗,詳盡分析了該檢測器的性能。
[Abstract]:Compared with the current magnetic sensors based on Fluxgate, Hall effect (Hall) and magnetic resistance effect, the GMI magnetic sensor based on the giant magnetic impedance effect (GMI) also has the advantages of high sensitivity, small volume, high response speed, Has the advantages of low magnetic hysteresis, low power consumption and the like, and has wide application prospect in the fields of weak magnetic field measurement and the like. At the same time, the magnetic anomaly detection (MAD) technology based on the earth's magnetic field has the characteristics of passive passive detection, good hiding performance, strong anti-interference ability and the like, and can be widely applied to the fields of resource exploration, transportation and military target detection and tracking. Therefore, the research of GMI magnetic sensor and magnetic field signal detection technology is of great theoretical significance and engineering application value. In this paper, the research on the design of the GMI magnetic sensor and the detection of the magnetic anomaly signal caused by the ferromagnetic target has been carried out in-depth. The main contents of this paper are as follows: (1) The GMI effect and its relation with the driving current frequency are briefly introduced. the frequency characteristic of the selected amorphous wire material is studied, the driving current frequency and the linear working range of the sensitive probe are selected according to the frequency characteristic, A signal conditioning circuit using an orthogonal lock difference circuit with strong noise suppression capability instead of a peak detection circuit as a GMI magnetic probe is proposed, the working principle of the signal conditioning circuit and the performance of the GMI magnetic sensor are analyzed in detail; in addition, According to the working principle of the active module such as the second generation current (CCII) and the transconductance operational amplifier (OTA), the present commercial chip AD844 is used to propose a dual-output quadrature sinusoidal oscillator with independent adjustable oscillation and resonant frequency. The working principle of the oscillator and the non-ideal condition analysis are introduced in detail. (2) The mathematical model of the magnetic anomaly detection is established, the expression of the magnetic anomaly signal based on the three orthogonal basis functions is derived in detail, and under the condition that the characteristic time of the target signal is known, according to the theory of the orthogonal matched filter bank, The magnetic anomaly detection system based on the orthogonal base function matching filter bank in the case of white noise is presented and described in detail, and based on this, The combination of the whitening filter and the orthogonal base function matching filter bank of the LMS adaptive AR model, which can be applied in the case of colored noise, is constructed and analyzed in detail. At the same time, for the case of 1/ f fractal noise as one of the main sources of the external magnetic field environment and the circuit, the pre-whitening effect of the adaptive whitening filter and the performance of the magnetic anomaly detection system are analyzed in detail by means of simulation and verification. At the same time, the feasibility and superiority of the detection system are further verified by using the measured data. (3) Based on the theory of the autoregressive-sliding average ARMA model, the auto-regressive integrated moving average (ARIMA) model which can be applied to the case of non-stationary time series and its establishment flow are introduced. and aiming at the situation that the characteristic time of the magnetic anomaly target signal is unknown and the background noise is a non-stationary time sequence, according to the L-step prediction formula of the ARMA model, a magnetic anomaly detection algorithm based on the ARIMA model prediction is proposed, The performance of the detection algorithm is analyzed in detail and its limitations are pointed out. At the same time, based on the theory of grey degree of association, a magnetic anomaly detection algorithm based on the combination of the residual of ARIMA model and the gray correlation degree is proposed, and its performance is analyzed in detail by means of simulation and verification. (4) The theory of discrete wavelet transform and inverse transform is introduced in brief. The concept of non-sampling discrete wavelet transform is derived for the problem of step-by-step reduction in the decomposition of the fast discrete wavelet transform. The local characteristics of time-domain and frequency-domain space are obtained by using the wavelet transform. Based on the principle of wavelet threshold de-noising, by analyzing the shortcomings of the traditional hard-threshold method and the soft-threshold method, a magnetic anomaly detection algorithm based on the wavelet threshold de-noising based on the weighted fuzzy function is proposed, The performance of the detection algorithm is analyzed in detail and the superiority of the algorithm is pointed out. In addition, using the characteristic of the wavelet transform to prewhiten the 1/ f noise, a magnetic anomaly detection algorithm based on the wavelet coefficient energy of the non-sampled discrete wavelet transform is proposed. The detection probability, false alarm probability and other theoretical expressions of the detection algorithm are derived in detail, and the performance of the detector is analyzed in detail through a series of simulation and verification experiments.
【學位授予單位】：國防科學技術(shù)大學
【學位級別】：博士
【學位授予年份】：2014
【分類號】：TN911.23;TP212.13

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