# Practical Accuracy Limits of Radiation-Aware Magneto-Inductive 3D Localization

## TL;DR

This paper investigates the practical accuracy limits of magneto-inductive 3D localization in indoor environments, considering real-world factors like field distortion and radiative effects, and demonstrates a median error of 3.2 cm.

## Contribution

It provides a comprehensive analysis of the factors affecting accuracy in magnetic localization systems and introduces a calibrated measurement approach including reactive and radiative propagation models.

## Key findings

- Median position error of 3.2 cm achieved
- Field distortion from building structures limits accuracy
- Predicted achievable accuracy using Cramér-Rao bound

## Abstract

The key motivation for the low-frequency magnetic localization approach is that magnetic near-fields are well predictable by a free-space model, which should enable accurate localization. Yet, limited accuracy has been reported for practical systems and it is unclear whether the inaccuracies are caused by field distortion due to nearby conductors, unconsidered radiative propagation, or measurement noise. Hence, we investigate the practical performance limits by means of a calibrated magnetoinductive system which localizes an active single-coil agent with arbitrary orientation, using 4 mW transmit power at 500 kHz. The system uses eight single-coil anchors around a 3m x 3m area in an office room. We base the location estimation on a complex baseband model which comprises both reactive and radiative propagation. The link coefficients, which serve as input data for location estimation, are measured with a multiport network analyzer while the agent is moved with a positioner device. This establishes a reliable ground truth for calibration and evaluation. The system achieves a median position error of 3.2 cm and a 90th percentile of 8.3 cm. After investigating the model error we conjecture that field distortion due to conducting building structures is the main cause of the performance bottleneck. The results are complemented with predictions on the achievable accuracy in more suitable circumstances using the Cram\'er-Rao lower bound.