A unified approach for hybrid source localization based on ranges and video

Ferreira, Beatriz Quintino; Gomes, João; Costeira, João Paulo

doi:10.1109/icassp.2015.7178497

Cited by 14 publications

(14 citation statements)

References 12 publications

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“…It is assumed that anchors exclusively are suitably equipped to acquire the AoA measurements (e.g. with directional antenna or antenna array [5], or video cameras [11]). Therefore, by applying simple geometry, azimuth and elevation angle measurements can be modeled respectively as [5]:…”

Section: Problem Formulationmentioning

confidence: 99%

Distributed RSS-AoA Based Localization With Unknown Transmit Powers

Tomic

Beko

Dinis

2016

IEEE Wireless Commun. Lett.

107

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Abstract-This letter addresses the hybrid range/angle-based target localization problem in a cooperative 3-D wireless sensor network where no central processor is available. Due to battery exhaust over time, sensors' transmit powers are assumed different and unknown. Range and angle measurements are drawn from the received signal strength and angle-of-arrival models, respectively. By exploiting the measurement models, we derive a novel local-estimator by which each target updates its own estimate, based on the least squares criterion. Second-order cone relaxation technique is then applied to approximately solve the attained problem due to its non-convex nature. Our simulation results show that the proposed algorithm efficiently solves the localization problem.Index Terms-Wireless localization, distributed localization, received signal strength (RSS), angle-of-arrival (AoA), second-order cone programming (SOCP), wireless sensor network (WSN).

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Section: Problem Formulationmentioning

confidence: 99%

Distributed RSS-AoA Based Localization With Unknown Transmit Powers

Tomic

Beko

Dinis

2016

IEEE Wireless Commun. Lett.

107

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“…Although TOA, DOA, and received signal strength (RSS) measurements were suggested as input data in [18], only RSS-based results were presented. Recent advances in cooperative hybrid (distance and direction) localization were presented in [19], [20]. The CLORIS algorithm, proposed in [19], employed a heuristic cost function, which was not derived from a statistical data model.…”

Section: Imentioning

confidence: 99%

“…Recent advances in cooperative hybrid (distance and direction) localization were presented in [19], [20]. The CLORIS algorithm, proposed in [19], employed a heuristic cost function, which was not derived from a statistical data model. In [20], a Gaussian data model was proposed for hybrid data, The Gaussian distribution is not generally suitable for DOA estimates as it has an infinite support instead of a periodic support of 2π over angular domain [21].…”

Section: Imentioning

confidence: 99%

A Bayesian Algorithm for Distributed Network Localization Using Distance and Direction Data

Naseri

Koivunen

2019

IEEE Trans. on Signal and Inf. Process. over Networks

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A reliable, accurate, and affordable positioning service is highly required in wireless networks. In this paper, the novel Message Passing Hybrid Localization (MPHL) algorithm is proposed to solve the problem of cooperative distributed localization using distance and direction estimates. This hybrid approach combines two sensing modalities to reduce the uncertainty in localizing the network nodes. A statistical model is formulated for the problem, and approximate minimum mean square error (MMSE) estimates of the node locations are computed. The proposed MPHL is a distributed algorithm based on belief propagation (BP) and Markov chain Monte Carlo (MCMC) sampling. It improves the identifiability of the localization problem and reduces its sensitivity to the anchor node geometry, compared to distance-only or direction-only localization techniques. For example, the unknown location of a node can be found if it has only a single neighbor; and a whole network can be localized using only a single anchor node. Numerical results are presented showing that the average localization error is significantly reduced in almost every simulation scenario, about 50% in most cases, compared to the competing algorithms.Notice: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.

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“…The relaxation is tight, yielding a high-accuracy estimate for the source position through matrix factorization. A description and preliminary performance characterization of this algorithm were presented in [3];…”

Section: Introductionmentioning

confidence: 99%

FLORIS and CLORIS: Hybrid source and network localization based on ranges and video

et al. 2018

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We propose hybrid methods for localization in wireless sensor networks fusing noisy range measurements with angular information (extracted from video). Compared with conventional methods that rely on a single sensed variable, this may pave the way for improved localization accuracy and robustness. We address both the single-source and network (i.e., cooperative multiple-source) localization paradigms, solving them via optimization of a convex surrogate. The formulations for hybrid localization are unified in the sense that we propose a single nonlinear least-squares cost function, fusing both angular and range measurements. We then relax the problem to obtain an estimate of the optimal positions. This contrasts with other hybrid approaches that alternate the execution of localization algorithms for each type of measurement separately, to progressively refine the position estimates. Single-source localization uses a semidefinite relaxation to obtain a one-shot matrix solution from which the source position is derived through factorization. Network localization uses a different approach where sensor coordinates are retained as optimization variables, and the relaxed cost function is efficiently minimized using fast iterations based on Nesterov's optimal method. Further, an automated calibration procedure is developed to express range and angular information, obtained through different devices, possibly deployed at different locations, in a single consistent coordinate system. This drastically reduces the need for manual calibration that would otherwise negatively impact the practical usability of hybrid range/video localization systems. We develop and test, both in simulation and experimentally, the new hybrid localization algorithms, which not only overcome the limitations of previous fusing approaches, but also compare favourably to state-of-the-art methods, even outperforming them in some scenarios.

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A unified approach for hybrid source localization based on ranges and video

Cited by 14 publications

References 12 publications

Distributed RSS-AoA Based Localization With Unknown Transmit Powers

Distributed RSS-AoA Based Localization With Unknown Transmit Powers

A Bayesian Algorithm for Distributed Network Localization Using Distance and Direction Data

FLORIS and CLORIS: Hybrid source and network localization based on ranges and video

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