Hybrid Cooperative Positioning Based on Distributed Belief Propagation

Caceres, Mauricio A.; Penna, Federico; Wymeersch, Henk; Garello, Roberto

doi:10.1109/jsac.2011.111205

Cited by 99 publications

(77 citation statements)

References 16 publications

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“…In this section, we will analyze the model (1) in some depth, shedding light on different impairments that were ignored in prior works [2], [9]. Based on our analysis, we describe our extended model in Section III-C.…”

Section: Pseudorange Availability In Low Snrmentioning

confidence: 99%

Hybrid Cooperative Positioning in Harsh Environments

Daniel

Wymeersch

Nurmi

2015

2015 IEEE Globecom Workshops (GC Wkshps)

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Hybrid cooperative positioning involves the combination of satellite pseudoranges with measurements based on terrestrial radio signals, with the aim to improve both coverage and accuracy. This paper presents a theoretical analysis of hybrid cooperative positioning in low signal-to-noise ratio environments, explicitly accounting for scenarios where receivers can receive signals but cannot decode navigation messages. We propose an extended pseudorange model, suitable for evaluation of measurements made by the receiver in these scenarios, as well as extended cooperation across agents attempting to enable satellite navigation functionality of receivers operating below signal-tonoise ratio threshold required for proper message decoding. The advantages of such extended cooperation are illustrated on a realistic scenario by means of the Cramér-Rao lower bound.

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Section: Pseudorange Availability In Low Snrmentioning

confidence: 99%

Hybrid Cooperative Positioning in Harsh Environments

Daniel

Wymeersch

Nurmi

2015

2015 IEEE Globecom Workshops (GC Wkshps)

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“…Two categories of hybrid CP algorithms have been recently introduced for wireless sensor networks (WSNs) localisation in order to increase the performance of CP in terms of accuracy. The first is based on graphical models [7,8] which is done in a distributed manner and is highly suitable for CP. However, the factor graph adds another burden in terms of computation complexity because of the sampling message that have to be evaluated in advance.…”

Section: Introductionmentioning

confidence: 99%

Hybrid global navigation satellite systems, differential navigation satellite systems and time of arrival cooperative positioning based on iterative finite difference particle filter

Georges¹,

Wang²,

Xiao³

et al. 2015

IET Communications

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In this study, the authors develop a novel solution for hybrid global navigation satellite systems, differential navigation satellite systems and time of arrival cooperative positioning (CP) based on iterative finite difference particle filter (PF) in GNSS-terrestrial navigation and challenging environments. A variant of finite difference filters called divided difference filter (DDF) was used as an importance density for particle generation. Various proposal distributions have been proposed to improve the performance of PF, but practical situations have encouraged the researchers to design better candidate for proposal distributions in order to gain better performance especially for hybrid CP system. The author's proposed method named hybrid cooperative particle-based DDF solves the problem of linearisation of non-linear functions that are based on Jacobian matrices which often cannot be applied in practical applications of non-linear estimation techniques. An iterative reweighted information filter based on the extended Kalman filter (KF) was integrated during the measurement update phase to smooth the output of the DDF used for particles update. Simulation results based on a realistic outdoor scenario show that the proposed solution outperforms some wellknown state-of-the-art in hybrid CP systems, such as hybrid cooperative unscented KF in terms of accuracy and availability and provides good performance even in challenging conditions.

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“…Assuming availability of a global navigation satellite systems (GNSS), work in [5] derives a hybrid distributed particle filter and posterior distributions are approximated as a single Gaussian distribution. Subsequent and relevant work can be found in [6] where posteriors are represented as a single multivariate Gaussian distribution, with parameters estimated through importance sampling, sample mean and variance estimators. In [7], UWB radios are assumed and parametric modeling of the posteriors is based on a single Gaussian or a mixture of two Gaussians, while other possible options are censored.…”

Section: Introductionmentioning

confidence: 99%

Narrowband cooperative network localization

Fasarakis-Hilliard

Alevizos

Bletsas

2014

2014 IEEE Global Communications Conference

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We consider the problem of distributed cooperative location estimation in motionless and mobile narrowband wireless sensor networks (WSNs), where network terminals (to be localized) are several hops away from the anchor nodes (with a priori known location). Such problem is inspired by practical setups where communication bandwidth is limited, as in underwater systems with narrow-band acoustic modems. A cooperative and distributed particle filter (Coop-PF) is designed, where network nodes exchange information locally, i.e. only with neighboring terminals. However, each node does not communicate particles. Instead, a combination of clustering, mixture models and parameterization of the communicated information is explored. The proposed approach improves performance compared to utilizing a fixed Gaussian mixture model and demonstrates accuracy comparable to state-of-the-art wideband cooperative localization, while achieving a two orders of magnitude reduction in communication. As a collateral dividend, a computationallyefficient version is also offered.

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Hybrid Cooperative Positioning Based on Distributed Belief Propagation

Cited by 99 publications

References 16 publications

Hybrid Cooperative Positioning in Harsh Environments

Hybrid Cooperative Positioning in Harsh Environments

Hybrid global navigation satellite systems, differential navigation satellite systems and time of arrival cooperative positioning based on iterative finite difference particle filter

Narrowband cooperative network localization

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