A collaborative method for positioning based on GNSS inter agent range estimation

Minetto, Alex; Cristodaro, Calogero; Dovis, Fabio

doi:10.23919/eusipco.2017.8081704

Cited by 10 publications

(7 citation statements)

References 11 publications

(11 reference statements)

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“…where X i,m is the m-th observation of the random variable X i . The correlation coefficients estimated through (29) are employed in the generalized theoretical Formula ( 24) to obtain a refined estimation of the IAR variance. As shown in Figure 17, taking into account the correlation between the measurements improved the match between the theoretical and experimental values.…”

Section: Validation Of the Theoretical Model Using Cots Receivermentioning

confidence: 99%

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Modelling and Experimental Assessment of Inter-Personal Distancing Based on Shared GNSS Observables

Minetto

Nardin

Dovis

2021

Sensors

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In the last few years, all countries worldwide have fought the spread of SARS-CoV-2 (COVID-19) by exploiting Information and Communication Technologies (ICT) to perform contact tracing. In parallel, the pandemic has highlighted the relevance of mobility and social distancing among citizens. The monitoring of such aspects appeared prominent for reactive decision-making and the effective tracking of the infection chain. In parallel to the proximity sensing among people, indeed, the concept of social distancing has captured the attention to signal processing algorithms enabling short-to-medium range distance estimation to provide behavioral models in the emergency. By exploiting the availability of smart devices, the synergy between mobile network connectivity and Global Navigation Satellite Systems (GNSS), cooperative ranging approaches allow computing inter-personal distance measurements in outdoor environments through the exchange of light-weight navigation data among interconnected users. In this paper, a model for Inter-Agent Ranging (IAR) is provided and experimentally assessed to offer a naive collaborative distancing technique that leverages these features. Although the technique provides distance information, it does not imply the disclosure of the user’s locations being intrinsically prone to protect sensitive user data. A statistical error model is presented and validated through synthetic simulations and real, on-field experiments to support implementation in GNSS-equipped mobile devices. Accuracy and precision of IAR measurements are compared to other consolidated GNSS-based techniques showing comparable performance at lower complexity and computational effort.

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Section: Validation Of the Theoretical Model Using Cots Receivermentioning

confidence: 99%

“…In particular, GNSS has been investigated by researchers to explore cooperative distance estimation [29]. In this framework, the distance between users can be computed indirectly, by leveraging GNSS raw data and a communication channel between cooperating users (namely the agents).…”

Section: Introductionmentioning

confidence: 99%

Modelling and Experimental Assessment of Inter-Personal Distancing Based on Shared GNSS Observables

Minetto

Nardin

Dovis

2021

Sensors

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“…Other DGNSSbased techniques are comparatively investigated in [25]. A further method was then proposed by relying on the exchange of both pseudorange measurements and the terms of the Direction Cosine Matrix (DCM) computed within the Position Time Velocity (PVT), in [26].In previous contributions, researchers observed remarkable improvement in CP by tightly integrating Double Differences (DD), and the quantity of information carried by such differential measurements was demonstrated in [22], [27]- [29].…”

Section: A Estimation and Integration Of Gnss Differential Range Measmentioning

confidence: 99%

“…First, a Hybrid Weighted Least Square (H-WLS)-based PVT is performed through a Self-Adaptive Iterative Algorithm (SAIA) proposed in [26] to cope with strong linear dependence of multiple inter-agent distances, thus to solve for ill-conditioned set of linear equations. Once the first fix is obtained, an indirect formulation of the EKF with periodic WLS re-initialization is in charge of a Bayesian positioning estimation, according to the scheme in Figure 5.…”

Section: Ekf Hybridization For Cp Tight Integrationmentioning

confidence: 99%

DGNSS Cooperative Positioning in Mobile Smart Devices: a Proof of Concept

Minetto¹,

Bello²,

Dovis³

2021

Preprint

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<div>In recent years positioning and navigation capabilities in mobile devices have become essential to the evergrowing number of position-related smart applications. Global Navigation Satellite System (GNSS) constitutes the provider for geo-localization, therefore consumer-grade, embedded GNSS receivers have become ubiquitous in mobile smart devices. Among these, smartphones play a dominant role in enabling such modern services based on position information. However, GNSS positioning shows several weaknesses in urban contexts where mobile smart devices are massively diffused. Indeed, the limited sky visibility and multipath scattering induced by buildings severely threat the quality of the final solution. Two main ingredients can enable innovative collaborative strategies capable to increase the robustness of GNSS navigation: The availability of raw GNSS measurements which have been recently disclosed in ultra-low cost smartphone chipsets and the ubiquitous connectivity provided by modern low-latency, network infrastructures allowing for near-real-time exchange of data. This work presents the architecture of a Proof Of Concept designed to demonstrate the feasibility of a GNSS-only Cooperative Positioning among networked smartphones equipped with GNSS receivers. The test campaign presented in this work assessed the feasibility of the approach over 4G/LTE network connectivity and an average accuracy improvement over the 40%.</div>

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“…The implementation of future cooperative algorithms will show the impact of the aiding user A on the positioning accuracy of user B compared to the reference trajectory. Future collaborative work around this scenario would be the computation of the estimate of the range between two users described in [18]. We expect to see a significant increase of positioning accuracy with the use of aiding techniques and algorithms.…”

Section: Iii2 -Preliminary Testingmentioning

confidence: 99%

An Assessment Methodology of Smartphones Positioning Performance for Collaborative Scenarios in Urban Environment

Verheyde¹,

Blais²,

Macabiau³

et al. 2020

Proceedings of the 33rd International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS+ 202

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Thomas VERHEYDE graduated from ENAC ("The French civil aviation university") with a Master of Science in Aerospace Systems Navigation & Telecommunication. Currently pursuing my PhD in the GNSS domain, my thesis' title is "Precise Cooperative Positioning of Low-Cost Mobiles in an Urban Environment". Employed by TéSA (Telecommunication Research Laboratory) in Toulouse and my research is co-funded by CNES (French space agency) and Thalès Alénia Space.Dr. Antoine BLAIS has earned an engineering degree from ENAC (École Nationale de l'Aviation Civile,

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A collaborative method for positioning based on GNSS inter agent range estimation

Cited by 10 publications

References 11 publications

Modelling and Experimental Assessment of Inter-Personal Distancing Based on Shared GNSS Observables

Modelling and Experimental Assessment of Inter-Personal Distancing Based on Shared GNSS Observables

DGNSS Cooperative Positioning in Mobile Smart Devices: a Proof of Concept

An Assessment Methodology of Smartphones Positioning Performance for Collaborative Scenarios in Urban Environment

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