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arXiv · 2507.04358

A note on Global Positioning System (GPS) and Euclidean distance matrices

A. Y. Alfakih
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Abstract

Let $D$ be an $n \times n$ Euclidean distance matrix (EDM) with embedding dimension $r$; and let $d \in R^n$ be a given vector. In this note, we consider the problem of finding a vector $y \in R^n$, that is closest to d in Euclidean norm, such that the augmented matrix $\left[ \begin{array}{cc} 0 & y^T \\ y & D \end{array}\right]$ is itself an EDM of embedding dimension $r$. This problem is motivated by applications in Global Positioning System (GPS). We present a fault detection criterion and three algorithms: one for the case $n=4$, and two for the case $n \geq 5$.

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A. Y. Alfakih. 2025-07-06. A note on Global Positioning System (GPS) and Euclidean distance matrices. https://arxiv.org/abs/2507.04358

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