Error Estimation for the Linearized Auto-Localization Algorithm

Sensors

Jorge Guevara¹  Antonio R. Jiménez²  Jose Carlos Prieto² 

[1] Centro de Automática y Robótica (CAR), Consejo Superior de Investigaciones Científicas (CSIC)-UPM, Ctra. Campo Real km 0.2, La Poveda-Arganda del Rey, 28500, Madrid, Spain;

关键词: auto-localization;    auto-calibration;    local positioning systems;    differential sensitivity analysis;    uncertainty propagation;   

DOI  :  10.3390/s120302561

来源: mdpi

【 摘 要 】

The Linearized Auto-Localization (LAL) algorithm estimates the position of beacon nodes in Local Positioning Systems (LPSs), using only the distance measurements to a mobile node whose position is also unknown. The LAL algorithm calculates the inter-beacon distances, used for the estimation of the beacons’ positions, from the linearized trilateration equations. In this paper we propose a method to estimate the propagation of the errors of the inter-beacon distances obtained with the LAL algorithm, based on a first order Taylor approximation of the equations. Since the method depends on such approximation, a confidence parameter τ is defined to measure the reliability of the estimated error. Field evaluations showed that by applying this information to an improved weighted-based auto-localization algorithm (WLAL), the standard deviation of the inter-beacon distances can be improved by more than 30% on average with respect to the original LAL method.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland