Anchor node placement for localization in wireless sensor networks

Tatham, Benjamin; Kunz, Thomas

doi:10.1109/wimob.2011.6085407

Cited by 21 publications

(21 citation statements)

References 10 publications

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“…Since CRLB ℓ1,ℓ2 < CRLB ℓ1,ℓ3 as stated in the proposition, the equalizer property in Corollary 1 implies that CRLB ℓ1,ℓ2 < CRLB ℓ1 (z opt ℓ1,ℓ3 ), which, via (25) and (50), leads to…”

Section: E Proof Of Propositionmentioning

confidence: 92%

“…where CRLB m (z) and CRLB n (z) are given by (25). First, based on Proposition 3, the following result is obtained for two target nodes (N T = 2) in the absence of distance constraints (i.e., ε → 0).…”

Section: Propositionmentioning

confidence: 95%

“…where the first inequality follows from CRLB ℓ1 (z opt ℓ1,ℓ2 ) < CRLB ℓ1 (z opt ℓ1,ℓ3 ) and (25), and the second inequality is by the definition of location z 1 (see Fig. 14-(b) for illustration).…”

Section: E Proof Of Propositionmentioning

confidence: 99%

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Optimal Jammer Placement in Wireless Localization Systems

Gezici

Bayram

Kurt

et al. 2016

IEEE Trans. Signal Process.

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In this study, the optimal jammer placement problem is proposed and analyzed for wireless localization systems. In particular, the optimal location of a jammer node is obtained by maximizing the minimum of the Cramer-Rao lower bounds (CRLBs) for a number of target nodes under location related constraints for the jammer node. For scenarios with more than two target nodes, theoretical results are derived to specify conditions under which the jammer node is located as close to a certain target node as possible, or the optimal location of the jammer node is determined by two of the target nodes. Also, explicit expressions are provided for the optimal location of the jammer node in the presence of two target nodes. In addition, in the absence of distance constraints for the jammer node, it is proved, for scenarios with more than two target nodes, that the optimal jammer location lies on the convex hull formed by the locations of the target nodes and is determined by two or three of the target nodes, which have equalized CRLBs. Numerical examples are presented to provide illustrations of the theoretical results in different scenarios.Comment: To appear in IEEE Transactions on Signal Processin

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Section: E Proof Of Propositionmentioning

confidence: 92%

Section: Propositionmentioning

confidence: 95%

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Optimal Jammer Placement in Wireless Localization Systems

Gezici

Bayram

Kurt

et al. 2016

IEEE Trans. Signal Process.

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“…Anchors placement layout It is well known in the literature that anchor placement layout has a significant impact on the localization accuracy [29,30]. Here, we study this impact on the effectiveness of EasyLoc trilateration method.…”

Section: Rss and Distance Mappingmentioning

confidence: 98%

EasyLoc: Plug-and-Play RSS-Based Localization in Wireless Sensor Networks

Jamâa

Koubâa

Baccour

et al. 2013

Studies in Computational Intelligence

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Localization based on Received Signal Strength (RSS) is a key method for locating objects in Wireless Sensor Networks (WSNs). However, current RSS-based methods are ineffective at both deployment and operation design levels. First, they usually require a labor-intensive pre-deployment profiling operations to map the RSS to either locations or distances. Second often rely on heavy processing operations. These two design problems limit the possibility of implementing such localization techniques on resource-constrained sensor nodes, and also restrict their scalability and use in practice. In this book chapter, we discuss the challenges and limitations of RSS-based localization mechanisms and we propose, EasyLoc, an autonomous and practical RSS-based localization technique that improves on previous approaches in terms of ease of deployment and ease of implementation, while still providing a reasonable accuracy. EasyLoc is a plug-and-play and fully distributed RSSbased localization method that requires zero pre-deployment configuration. The idea consists in exploiting the available distance information between anchors to derive an online and anchor-specific RSS to distance mapping. We show that, in addition to its simplicity, EasyLoc provides, in the best case, a reasonable average distance error of 2 m in an indoor environment of 30 m 2 .

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“…The coil placement, similar to the general problem of anchor node placement in wireless sensor networks [26,27], was an important consideration in our work. While a symmetrical distribution of the coils is not essential, equidistant placement of the coils helps in making sure that in every possible sensor position in the tank there is a minimum of three coils that generate fields of sufficient strength for proper localization.…”

Section: Demonstrator and Integration Issuesmentioning

confidence: 99%

Neural Virtual Sensors for Adaptive Magnetic Localization of Autonomous Dataloggers

Groben

Thongpull

Kammara

et al. 2014

Advances in Artificial Neural Systems

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The surging advance in micro-and nanotechnologies allied with neural learning systems allows the realization of miniaturized yet extremely powerful multisensor systems and networks for wide application fields, for example, in measurement, instrumentation, automation, and smart environments. Time and location context is particularly relevant to sensor swarms applied for distributed measurement in industrial environment, such as, for example, fermentation tanks. Common RF solutions face limits here, which can be overcome by magnetic systems. Previously, we have developed the electronic system for an integrated data logger swarm with magnetic localization and sensor node timebase synchronization. The focus of this work is on an approach to improving both localization accuracy and flexibility by the application of artificial neural networks applied as virtual sensors and classifiers in a hybrid dedicated learning system. Including also data from an industrial brewery environment, the best investigated neural virtual sensor approach has achieved an advance in localization accuracy of a factor of 4 compared to state-of-the-art numerical methods and, thus, results in the order of less than 5 cm meeting industrial expectations on a feasible solution for the presented integrated localization system solution.

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Anchor node placement for localization in wireless sensor networks

Cited by 21 publications

References 10 publications

Optimal Jammer Placement in Wireless Localization Systems

Optimal Jammer Placement in Wireless Localization Systems

EasyLoc: Plug-and-Play RSS-Based Localization in Wireless Sensor Networks

Neural Virtual Sensors for Adaptive Magnetic Localization of Autonomous Dataloggers

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