Search arXivSearch

arXiv · 2509.24683

Impedance Modeling of Magnetometers: A Path Toward Low-Noise Readout Circuits

Abstract

Optimizing sensor readout schemes and integrated circuit designs for both open-loop and closed-loop implementations requires precise modeling and simulation strategies. This study introduces a novel two-port impedance model to estimate the behavior of a converse Magnetoelectric (cME) sensor. This model provides a possible framework for calculating transfer functions and simulating magnetometer behavior in both continuous- and discrete-time simulation environments, and it is also possibly transferable to other magnetometer types. Common S-parameters were measured experimentally using an impedance analyzer and converted to Z-parameters to create a transfer function for system-level simulations. The model was validated through an analysis of output-related noise using MATLAB and LTSpice simulations to optimize the noise of the analog circuit parts of the system. The simulation results were compared with experimental measurements using a Zurich Instruments lock-in amplifier and the custom-designed low-noise printed circuit board (PCB) under model considerations. The proposed methodology derives noise considerations and the transfer function of a magnetometer. These are essential for readout schemes for mixed-signal circuit design. This allows low-noise electronics to be designed and extended to other sensor interface electronics, broadening their applicability in high-performance magnetic sensing.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Johan Arbustini, Eric Elzenheimer, Elizaveta Spetzler, Pablo Mendoza, Daniel Fernández, Jordi Madrenas, Jeffrey McCord, Michael Höft, Robert Rieger, Andreas Bahr. 2025-09-29. Impedance Modeling of Magnetometers: A Path Toward Low-Noise Readout Circuits. https://arxiv.org/abs/2509.24683

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Circulant ADMM-Net for Fast High-resolution DoA Estimation

This paper introduces CADMM-Net and CHADMM-Net, two deep neural networks for direction of arrival estimation within the least-absolute shrinkage and selection operator (LASSO) framework. These two networks are based on a structured deep unfolding of the alternating direction method of multipliers (ADMM) algorithm through the use of circulant as well as Hermitian-circulant matrices. Along with a computational complexity of $\mathcal{O}(N\log(N))$ per layer for the inference, where $N$ is the length of the dictionary $\mathbf{A}$, they additionally exhibit a memory footprint of $N$ and approximately half of $N$ for CADMMNet and CHADMM-Net, respectively, compared with $N^{2}$ for ADMM-Net. Furthermore, these structured networks exhibit a competitive performance against ADMM-Net, LISTA, TLISTA, and THLISTA with respect to the detection rate, the angular root-mean square error, and the normalized mean squared error.

eess.SP

BASIIS: Bistatic Angular Sampling and Interpolation for ISAC Setups

Integrated Sensing and Communications (ISAC) is a defining feature of 6G, extending cellular networks with radar-like sensing at limited additional overhead. In bistatic deployments, sensing requires coordinating the transmitter (TX) and receiver (RX) arrays to scan the Cartesian product of angle of departure and arrival, resulting in a four-dimensional sampling problem in the angular domain. This work establishes a complete angular sampling framework for bistatic ISAC, extending the DFT-based optimal-sampling methodology to the full azimuth and elevation domains of both arrays. We show that the bistatic geometry couples the TX and RX elevation angles, and represent this coupling through the ortho-baseline coarray, a virtual array that captures the joint elevation aperture of the array pair. From the coarray we derive a minimal sampling and interpolation scheme, near-lossless and realizable with any beamforming architecture. Monte Carlo simulations confirm the proposed minimal acquisition essentially equalizes the detection accuracy of dense oversampled imaging while acquiring 3 to 5 times fewer TX-RX direction pairs. This allows having bistatic operations with drastically reduced overhead on the radio resource usage of ISAC systems.

eess.SP

Centroid Angle Estimation of Multiple Scatterers Using Monopulse Radar with Frequency Diversity

The monopulse technique determines the angle of a target by comparing signals from two narrow beams, yielding a precise angular estimate with low complexity. However, it struggles to resolve multiple closely spaced scatterers within the same resolution cell. Existing methods for estimating multiple scatterer angles involve complex signal processing and system modifications. We propose an effective method to estimate the angular centroid of scatterers using the mode of monopulse angle estimates. A semi-analytic expression for the angle estimate distribution is derived, confirming that its mode aligns with the centroid. To enhance estimation accuracy, we employ frequency diversity to reduce sample correlation. Numerical results validate the advantages of the proposed method, demonstrating superior performance over conventional techniques with low complexity.

eess.SP