Joint localization and clock synchronization for wireless sensor networks

Chepuri, Sundeep Prabhakar; Leus, Geert; Veen, Alle‐Jan van der

doi:10.1109/acssc.2012.6489262

Cited by 18 publications

(10 citation statements)

References 7 publications

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“…The listed methods consider asynchronity in clock skew and phase, and determine the unknown location of source nodes in a two dimensional space by means of anchor nodes at known locations. They mainly differ in the solution strategy (e.g., least squares, message passing, ...) and if the estimation is performed by a central computation unit [2]- [4] or in a distributed manner [4]- [6]. However, all methods require that anchors and source nodes actively participate in a predefined protocol, where the minimum requirement is the exchange of receive and transmit time information, or responding a round-trip request.…”

Section: Introductionmentioning

confidence: 98%

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Passive localization and synchronization in the presence of affine clocks

Etzlinger

Pimminger

Fischereder

et al. 2015

2015 49th Asilomar Conference on Signals, Systems and Computers

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We consider the passive localization problem in a wireless network, where source nodes at unknown positions are emitting arbitrary signals at unknown time. The receiving asynchronous anchor nodes act passively as they do not cooperate with the source nodes. In order to localize the source nodes, the local receive times from the anchors are collected at a central processing unit. As the estimation of the location also involves the unknown clock parameters and the send times as variables, it is difficult to directly compute a maximum a-posterior estimate. Here, we derive a low-complex iterative solution based on the expectation-maximization algorithm. In contrast to previous works, we consider asynchronity in clock offset and skew by using an affine clock model. By numerical analysis we demonstrate that the proposed scheme performs close to the CRLB and is applicable to scenarios, where the employment field of source nodes is bounded by anchor nodes.

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Section: Introductionmentioning

confidence: 98%

“…Consequently, a number of simultaneous localization and synchronization algorithms were proposed recently [2]- [6]. The listed methods consider asynchronity in clock skew and phase, and determine the unknown location of source nodes in a two dimensional space by means of anchor nodes at known locations.…”

Section: Introductionmentioning

confidence: 99%

Passive localization and synchronization in the presence of affine clocks

Etzlinger

Pimminger

Fischereder

et al. 2015

2015 49th Asilomar Conference on Signals, Systems and Computers

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“…Because distance estimates, which are the basis of many localization methods, are often obtained from time-of-arrival estimates, localization and synchronization tasks are tightly interconnected [4], [5]. This interconnection is leveraged by the distributed algorithms for cooperative simultaneous localization and synchronization (CoSLAS) that were recently proposed in [6], [7].…”

Section: Introductionmentioning

confidence: 99%

Cooperative simultaneous localization and synchronization: Toward a low-cost hardware implementation

Etzlinger

Meyer

Wymeersch

et al. 2014

2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)

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Cooperative sensor self-localization (CSL) in wireless networks usually requires the nodes to be equipped with specific ranging hardware including ultra-wideband or ultrasonic distance sensors. Such designs are not suitable for application in low-cost, low-power sensor networks. Here, we demonstrate how low-cost, low-power, asynchronous sensor nodes can be used to perform CSL (and, simultaneously, distributed synchronization) by means of time-stamped communication without additional ranging hardware. Our method combines a belief propagation message passing algorithm for cooperative simultaneous localization and synchronization (CoSLAS) with a MAC-layer time stamping scheme. We validate the models underlying the CoSLAS algorithm by means of measurements, and we demonstrate that the localization accuracy achieved by our hardware implementation is far better than that corresponding to the time resolution and measurement errors of the hardware.

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“…Practical implementations and the combination of recently proposed methods from both fields are analyzed. In Chapter 6, an overview of simultaneous approaches is presented, with a distinction in centralized and distributed computation [1,19,26,35,36,37,75,89,124,129,137,138,139,141,143,144]. In this review we provide a comprehensive orientation in this novel topic.…”

Section: Introductionmentioning

confidence: 99%