Abstract
Ubiquitous global positioning is not feasible by GNSS alone, as it lacks accurate position fixes in dense urban centres and indoors. Hybrid positioning methods have been developed to aid GNSS in those environments. Fingerprinting localization in wireless local area networks (WLANs) is a promising aiding system because of its availability, accuracy, and error mechanisms opposed to that of GNSS. This article presents a low-cost approach to ubiquitous, seamless positioning based on a particle filter integrating GNSS pseudoranges and WLAN received signal strength indicators (RSSIs). To achieve accurate location estimates indoors/outdoors and in the transition zones, appropriate likelihood functions are essential as they determine the influence of each sensor information on the position estimate. We model the spatial RSSI distributions with Gaussian processes and use these models to predict RSSIs at the particle’s positions to obtain point estimates of the RSSI likelihood function. The particle filter’s performance is assessed with real data of two test trajectories in an environment challenging for GNSS and WLAN fingerprinting localization. Outcomes of an extended Kalman filter using pseudoranges and a WLAN position as observation is included as benchmark. The proposed algorithm achieves accurate and robust seamless localization with a median accuracy of five meters.
Highlights
The global navigation satellite system (GNSS) is present in almost all domains of modern life and it provides the base for many applications and services ranging from transportation and logistics, via surveying and mapping, to an uncountable number of leisure activities
We present a particle filter that integrates pseudoranges and received signal strength indicators (RSSIs) based on their likelihood functions, where a particle approximation of the signal strength likelihood function is obtained from a Gaussian process regression model
This study presents a new algorithm combining GPS pseudoranges and wireless local area networks (WLANs) RSSIs
Summary
The global navigation satellite system (GNSS) is present in almost all domains of modern life and it provides the base for many applications and services ranging from transportation and logistics, via surveying and mapping, to an uncountable number of leisure activities. GNSS alone is unable to satisfy many location based services. A common strategy to achieve robust ubiquitous positioning is to support GNSS with additional sensor information. Positioning systems based upon wireless local area networks (WLAN) are emerging from the large amount of options [2, 3]. This is due to the global dissemination of WLAN infrastructure (limiting the costs of its exploitation) and WLAN enabled devices and the trade-off between range and potential positioning accuracy
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