Abstract
We present a system for active noise control of environmental magnetic fields based on a filtered-x least mean squares algorithm. The system consists of a sensor that detects the ambient field noise and an error sensor that measures the signal of interest contaminated with the noise. These signals are fed to an adaptive algorithm that constructs a physical anti-noise signal canceling the local magnetic field noise. The proposed system achieves a maximum of 35 dB root-mean-square noise suppression in the DC-1kHz band and 55 and 50 dB amplitude suppression of 50 and 150Hz AC line noise, respectively, for all three axial directions of the magnetic vector field.
Highlights
Low noise environments are important across many metrologically relevant areas ranging from medical imaging of biomagnetic fields from the heart and brain to non-destructive evaluation of car batteries.1–5 Currently, optically pumped magnetometers (OPMs) are state of the art magnetic field sensors and are a promising alternative to conventional superconducting quantum interference device (SQUID) and fluxgate magnetometers in both shielded and unshielded conditions.6–10 A wider adoption of quantum magnetometers for ultra-low field precision measurements has been limited to magnetically shielded environments due to large external magnetic field noise, making such setups expensive
Active noise control (ANC) reduces the ambient magnetic field noise which in turn reduces the OPM linewidth increasing its sensitivity, enabling its operation in otherwise environmentally noisy conditions. This has additional implications in gradiometric magnetic field measurements using OPMs where the performance relies on the high common-mode-noise-rejection ratio (CMMR)
infinite-impulse response (IIR) filters have a slower rate of convergence for the adaptive algorithm than finite-impulse response (FIR) filters, which can result in adaptive stalling resulting in the poor performance of noise suppression
Summary
Low noise environments are important across many metrologically relevant areas ranging from medical imaging of biomagnetic fields from the heart and brain to non-destructive evaluation of car batteries. Currently, optically pumped magnetometers (OPMs) are state of the art magnetic field sensors and are a promising alternative to conventional superconducting quantum interference device (SQUID) and fluxgate magnetometers in both shielded and unshielded conditions. A wider adoption of quantum magnetometers for ultra-low field precision measurements has been limited to magnetically shielded environments due to large external magnetic field noise, making such setups expensive. The secondary source is driven by an electronic system that utilizes a specific signal processing algorithm (such as an adaptive algorithm) for the particular cancellation scheme (see Fig. 1) This technique is widely exploited in noise canceling headphone technology, vibration control, and exhaust ducts in ventilation and cooling systems.. While adaptive filtering techniques have been demonstrated in unwanted noise cancellation of electric and magnetic fields in the context of electrocardiography (ECG) and magnetocardiography (MCG), the noise cancellation was performed on the acquired data.. ANC reduces the ambient magnetic field noise which in turn reduces the OPM linewidth increasing its sensitivity, enabling its operation in otherwise environmentally noisy conditions. This has additional implications in gradiometric magnetic field measurements using OPMs where the performance relies on the high common-mode-noise-rejection ratio (CMMR)..
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