Robust and low complexity bayesian data fusion for hybrid cooperative vehicular localization

Hoang, Gia-Minh; Denis, Benoit; Härri, Jérôme; Slock, Dirk TM
ICC 2017, IEEE International Conference on Communications, May 21-25, 2017, Paris, France

This paper addresses Particle Filter (PF)-based hybrid Cooperative Localization (CLoc) strategies consisting of fusing absolute position information from embedded Global Navigation Satellite System (GNSS) with relative distance-dependent estimates using Impulse Radio - Ultra WideBand (IR-UWB) technology. Such hybrid GNSS/IR-UWB CLoc yet cannot benefit from the high precision estimates from the IR-UWB due to
the disparity between GNSS position and IR-UWB V2V range measurement noises, leading to a divergence in CLoc accuracy. This paper first investigates the source of such counter-intuitive effect, and second proposes a novel adaptive Bayesian dithering
technique to improve the efficiency of GNSS/IR-UWB fusionbased CLoc. This strategy increases the probability to reach a 20 cm accuracy from 50% (conventional IR-UWB and WiFi PF) to 95%.

DOI
Type:
Conference
City:
Paris
Date:
2017-05-21
Department:
Communication systems
Eurecom Ref:
5138
Copyright:
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