Abstract
A new algorithm for determining soft range information in network localization is proposed. It applies a variant of neural networks called mixture density networks. When used in particle-based Bayesian localization procedures, it has a similar low computational complexity and provides comparable localization accuracy as existing methods. This property enables the proposed algorithm to be implemented on low-power wireless sensor network (WSN) nodes that are equipped with commercial ultra-wideband transceivers. The proposed algorithm is validated in indoor network localization experiments.
Originalsprache | Englisch |
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Seiten | 1-5 |
Seitenumfang | 5 |
DOIs | |
Publikationsstatus | Veröffentlicht - 21 Juli 2020 |
Veranstaltung | 2020 IEEE International Conference on Communications Workshops (ICC Workshops) - Dublin, Ireland Dauer: 7 Juni 2020 → 11 Juni 2020 |
Konferenz
Konferenz | 2020 IEEE International Conference on Communications Workshops (ICC Workshops) |
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Zeitraum | 7/06/20 → 11/06/20 |