Soft Range Information for Network Localization

The demand for accurate localization in complex environments continues to increase despite the difficulty in extracting positional information from measurements. Conventional range-based localization approaches rely on distance estimates obtained from measurements (e.g., delay or strength of receive...

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Veröffentlicht in:	IEEE transactions on signal processing 2018-06, Vol.66 (12), p.3155-3168
Hauptverfasser:	Mazuelas, Santiago, Conti, Andrea, Allen, Jeffery C., Win, Moe Z.
Format:	Artikel
Sprache:	eng
Schlagworte:	Atmospheric measurements Detectors machine learning Machine learning algorithms network localization Particle measurements Position measurement Signal processing algorithms Soft range information Wireless communication wireless propagation
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