SNR enhancement of magnetic fields measurement with the diamond NV center using a compound filter system
At a Glance
Section titled âAt a Glanceâ| Metadata | Details |
|---|---|
| Publication Date | 2023-01-01 |
| Journal | Chinese Optics Letters |
| Authors | An Ye, Dingyuan Fu, Mingming Wu, Jiahao Guo, T. Y. Sheng |
| Institutions | East China University of Science and Technology |
| Citations | 3 |
| Analysis | Full AI Review Included |
Executive Summary
Section titled âExecutive SummaryâThis research introduces a novel compound filter system to significantly enhance the Signal-to-Noise Ratio (SNR) in diamond Nitrogen-Vacancy (NV) center magnetometry, particularly for weak magnetic field measurements.
- Core Innovation: A compound digital filter combining wavelet threshold denoising and a Normalized Least Mean Square (NLMS) adaptive filter is applied to Optically Detected Magnetic Resonance (ODMR) signals.
- Performance Gain (Weak Field): The system achieved an average SNR enhancement of 17.80 dB when measuring a weak 50 nT magnetic field across the 500 mHz to 100 Hz frequency range.
- Performance Gain (Low Frequency): An average SNR enhancement of 14.76 dB was demonstrated at a fixed low frequency (500 mHz) across a field range of 50 nT to 1100 nT.
- Fidelity: The compound filter system exhibited superior signal preservation, achieving 97.77% fidelity for the desired signal, surpassing conventional methods like the Butterworth filter (96.97%).
- Noise Mitigation: The system effectively removes high-frequency interference noise, complementing the low-frequency noise reduction achieved by standard differential measurement techniques.
- Operational Advantage: The adaptive filter component automatically adjusts its parameters (optimized using SNR feedback) to maintain optimal filtering performance in unknown or changing noise environments.
Technical Specifications
Section titled âTechnical Specificationsâ| Parameter | Value | Unit | Context |
|---|---|---|---|
| Excitation Wavelength | 532 | nm | NV center illumination |
| Bias Magnetic Field (B0) | ~70 | G | Provided by external magnets |
| Measured Magnetic Field Range | 50 to 1100 | nT | Weak field testing range |
| Sampling Rate | 100 | kSa/s | Data acquisition speed |
| Maximum SNR Achieved | 21.86 | dB | Optimized compound filter performance |
| SNR Enhancement (Weak Field) | 17.80 | dB | Average, at 50 nT (500 mHz to 100 Hz) |
| SNR Enhancement (Low Freq) | 14.76 | dB | Average, at 500 mHz (50 nT to 1100 nT) |
| Signal Fidelity (Compound Filter) | 97.77 | % | Preservation of desired signal features |
| Optimal NLMS Step Size (Âľ) | 0.69 | a.u. | Adaptive filter parameter |
| Optimal NLMS Constant (δ) | 0.012 | a.u. | Adaptive filter parameter |
| Wavelet Function (Initial Denoising) | Symlet 6 | N/A | Selected for preserving real signal features |
| Wavelet Function (Adaptive Reference) | Symlet 2 | N/A | Used for generating reference noise signal |
Key Methodologies
Section titled âKey MethodologiesâThe NV magnetometry experiment utilizes a continuous wave (CW) ODMR setup followed by a three-stage digital signal processing methodology:
-
CW ODMR Setup:
- A 532 nm laser excites the NV centers in the diamond.
- Microwave (MW) fields are delivered via a printed circuit board (PCB) antenna.
- Fluorescence is collected by a photodiode and demodulated using a lock-in amplifier (Zurich Instruments HF2LI).
- A bias magnetic field of approximately 70 G is applied along the NV axis using external magnets.
-
Differential Measurement:
- An auxiliary photodiode monitors the laser power ripple (noise source).
- This laser noise variation is subtracted from the collected fluorescent signal in the time domain. This step significantly improves sensitivity at low frequencies but is limited by electronics noise at high frequencies.
-
Wavelet Threshold Denoising (First Stage Filter):
- The differential signal is processed using a wavelet threshold denoising method.
- The Symlet 6 wavelet function is selected for its ability to preserve the real signal while denoising.
- This stage yields the âoriginal wavelet filtered signal.â
-
Adaptive Filtering (Second Stage Filter):
- The Normalized Least Mean Square (NLMS) algorithm is implemented as the adaptive filter, chosen for its rapid convergence and low instantaneous output error.
- Input Paths: The adaptive filter uses two inputs:
- Main Input: The original wavelet filtered signal s(n).
- Reference Input: An artificial reference signal d(n) generated by applying a second wavelet transform (Symlet 2, decomposition level 8) to the main input. This reference signal approximates the residual noise n0(n).
- Output: The residual error e(n) = s(n) - y(n) is the final filtered signal, where y(n) is the adaptive filter output minimizing the noise component.
-
Parameter Optimization:
- The adjustable parameters of the NLMS filter (step size ¾ and constant δ) are optimized by iteratively evaluating the resulting SNR enhancement. Optimal parameters were determined to be ¾ = 0.69 and δ = 0.012.
Commercial Applications
Section titled âCommercial ApplicationsâThe enhanced sensitivity and noise reduction achieved by this compound filter system are critical for advancing NV diamond-based quantum sensing technologies in several high-resolution fields:
- Quantum Sensing and Metrology: Enabling real-time, high-resolution measurement of weak magnetic fields, pushing the limits of room-temperature quantum sensors.
- Biomagnetism and Medical Imaging: Improving the detection quality for applications such as:
- Single-neuron action potential detection.
- Tumor tissue imaging (immunomagnetic microscopy).
- High-fidelity measurement of biological magnetic fields.
- Materials Science and Geoscience: Enhancing the resolution and reliability of micrometer-scale magnetic imaging for geological samples and advanced materials characterization.
- General Sensor Signal Processing: The combined wavelet-adaptive filter approach is highly transferable to other sensor systems (e.g., optical, acoustic, electrical) where high-fidelity signal extraction is required from noisy, non-stationary data (e.g., active noise control, ECG analysis).
View Original Abstract
Nitrogen-vacancy (NV) centers in diamond are progressively favored for room-temperature magnetic field measurement. The signal to noise ratio (SNR) optimization for NV diamond magnetometry generally concentrates on signal amplitude enhancement rather than efficient noise processing. Here, we report a compound filter system combining a wavelet denoising method and an adaptive filter for the realization of an efficient weak magnetic measurement with a high SNR. It allows enhanced magnetic field measurement with an average SNR enhancement of 17.80 dB at 50 nT within 500 mHz to 100 Hz and 14.76 dB at 500 mHz within 50 nT to 1100 nT. The introduction of this system in NV diamond magnetometry is aimed to improve signal quality by effectively eliminating the noise and retaining ideal signals.
Tech Support
Section titled âTech SupportâOriginal Source
Section titled âOriginal SourceâReferences
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