Universal Calibration Framework for Localization Infrastructures Using Distance-Only Measurements

Building on our previous work in 2D node mapping, this paper extends and generalizes the methodology to 3D, enabling the reconstruction of relative spatial configurations using only inter-node distance measurements. This approach leverages minimal ranging information, offering a simple and lightweight calibration tool for localization infrastructures. We formalize the problem, define the theoretical upper bound for the noise-to-distance ratio, and establish the maximum allowable deviation from the motions prescribed by the algorithm. While no real-world experiments are included, simulation results validate the mathematical framework, with prior work confirming the effectiveness of both the concept and the technology through experimental validation.