Body Shadowing Mitigation Using Differentiated LOS/NLOS Channel Models for RSSI-Based Monte Carlo Personnel Localization

Provided by: Institute of Electrical & Electronic Engineers
Topic: Mobility
Format: PDF
Research into localization has produced a wealth of algorithms and techniques to estimate the location of wireless network nodes, however the majority of these schemes do not explicitly account for non-line of sight conditions. Disregarding this common situation reduces their accuracy and their potential for exploitation in real world applications. This is a particular problem for personnel tracking where the user's body itself will inherently cause time-varying blocking according to their movements. Using empirical data, this paper demonstrates that, by accounting for non-line of sight conditions and using received signal strength based Monte Carlo localization, meter scale accuracy can be achieved for a wrist-worn personnel tracking tag in a 120 m2 indoor office environment.

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