A Theoretical Analysis of Mobility Detection in Connectivity-Based Localization for Short-Range Networks

Sangwoo Lee, Ilmu Byun, Sungjin Kim and Sunwoo Kim
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Sangwoo Lee: KPS Technology Team, Korea Aerospace Research Institute, Daejeon 34133, Korea
Ilmu Byun: Korea Railroad Research Institute, Uiwang 16105, Korea
Sungjin Kim: Department of Electronics and Computer Engineering, Hanyang University, Seoul 04763, Korea
Sunwoo Kim: Department of Electronics and Computer Engineering, Hanyang University, Seoul 04763, Korea

Energies, 2021, vol. 14, issue 4, 1-15

Abstract: This paper presents a theoretical analysis of mobility detection in connectivity-based localization, which exploits connectivity information as range measurements to anchors at a known location, to investigate how well and how precise mobility can be detected with connectivity in short-range networks. We derive mobility detection, miss detection, and false alarm probabilities in terms of a mobility detection threshold, defined as the minimum distance to detect the mobility, under the shadow fading channel and arbitrary mobility models to take into account practical and general scenarios. Based on the derivations, we address the threshold determination with the criteria in the sense of the minimum average error from miss detection and false alarm. Numerical and simulation evaluations are performed to verify our theoretical derivations, to show that increasing anchor numbers can improve the mobility detection probability with a smaller detection threshold, and that the probabilities are bounded by the weights of miss detection and false alarm. This work is the first attempt at addressing the performance of mobility detection using connectivity, and it can be utilized as a baseline for connectivity-based mobility tracking.

Keywords: connectivity-based localization; mobility detection; mobility tracking; theoretical analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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