An Event-Based Kalman Filter for Clock Synchronization

Giorgi, Giada

doi:10.1109/tim.2014.2340631

Cited by 25 publications

(20 citation statements)

References 30 publications

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“…Additionally, they are only discrete samples of continuous time. According to the above formula, the discrete-time clock offset is obtained by [ 29 , 30 ]:

where

represents the sampling index and

is the k th sampling period.…”

Section: Kalman Filter Based Clock Modelmentioning

confidence: 99%

ARS: Adaptive Robust Synchronization for Underground Coal Wireless Internet of Things

Zhang

Pang

Yin

et al. 2020

Sensors

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Clock synchronization is still a vital and challenging task for underground coal wireless internet of things (IoT) due to the uncertainty of underground environment and unreliability of communication links. Instead of considering on-demand driven clock synchronization, this paper proposes a novel Adaptive Robust Synchronization (ARS) scheme with packets loss for mine wireless environment. A clock synchronization framework that is based on Kalman filtering is first proposed, which can adaptively adjust the sampling period of each clock and reduce the communication overhead in single-hop networks. The proposed scheme also solves the problem of outliers in data packets with time-stamps. In addition, this paper extends the ARS algorithm to multi-hop networks. Additionally, the upper and lower bounds of error covariance expectation are analyzed in the case of incomplete measurement. Extensive simulations are conducted in order to evaluate the performance. In the simulation environment, the clock accuracy of ARS algorithm is improved by 7.85% when compared with previous studies for single-hop networks. For multi-hop networks, the proposed scheme improves the accuracy by 12.56%. The results show that the proposed algorithm has high scalability, robustness, and accuracy, and can quickly adapt to different clock accuracy requirements.

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“…Additionally, they are only discrete samples of continuous time. According to the above formula, the discrete-time clock offset is obtained by [ 29 , 30 ]:

where

represents the sampling index and

is the k th sampling period.…”

Section: Kalman Filter Based Clock Modelmentioning

confidence: 99%

ARS: Adaptive Robust Synchronization for Underground Coal Wireless Internet of Things

Zhang

Pang

Yin

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…It requires a high rate exchange of timing packets reducing the available bandwidth for the applications and its timing performance can be affected in extreme conditions such as network congestion. The latter [30] proposes a different clock servo loop based on the Kalman filter which is able to calculate the synchronization uncertainty improving the timestamp accuracy.…”

Section: White Rabbit Synchronization Protocolmentioning

confidence: 99%

A Fully Programmable White-Rabbit Node for the SKA Telescope PPS Distribution System

Jiménez-López

Torres-Gonzalez

Gutierrez-Rivas

et al. 2019

IEEE Trans. Instrum. Meas.

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Distributed data acquisition (DAQ) systems are in charge of converting different analog environment signals into digital values to perform control and monitor tasks. They require a computer network technology to share data between their different elements. One of their main issues is to match data with the specific events under study. A possible solution is to include an event synchronization technology such as Network Time Protocol (NTP), Precise Time Protocol (PTP), or White Rabbit (WR). This contribution proposes a high-performance distributed timing system based on the WR technology. We focus on the square kilometer array (SKA) project as an example of the distributed DAQ system. The SKA project has a strict timing requirements for its operation with a performance below 2 ns. This accuracy is not achievable by current standard synchronization technologies such as NTP or PTP. Under this context, the authors propose the WR zynq embedded node (WR-ZEN) platform as a candidate for the SKA's pulse per second (PPS) distribution system. It is a new design that integrates the WR technology, thus enabling the subnanosecond accuracy. Finally, the WR-ZEN has been evaluated in different scenarios to demonstrate its timing performance in dynamic environment conditions fulfilling the SKA telescope requirements for PPS distribution.

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“…These frequency accuracies are known to be related to the possible bounds of the clock skew. ), although there are algorithms that have explored more sophisticated models [ 18 , 22 ] and coped in a natural way with the variation of frequency (named skew) through signal processing [ 14 ]. However, these approaches do not provide hard guarantees due to their statistical nature.…”

Section: Introductionmentioning

confidence: 99%

“…The offset estimation algorithm works with a moving window for better adapting to changing drifts. It does not provide any measure of uncertainty in the estimate, but it usually achieves millisecond precision [22]. Its estimations assume symmetric communications.…”

mentioning

confidence: 99%

“…Its estimations assume symmetric communications. An evolution of NTP is PTP ("Precision Clock Synchronization Protocol", IEEE standard 1588 [30]); although this protocol can provide much better synchronization than NTP (below microseconds [22]) under the same symmetry assumption, it is used in special-purpose industrial automation and measurement networks since it requires specific hardware (e.g., high-speed Ethernet LAN) with automatic timestamping, which is prohibitive for most pairwise systems.…”

mentioning

confidence: 99%

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Characterization, Statistical Analysis and Method Selection in the Two-Clocks Synchronization Problem for Pairwise Interconnected Sensors

Fernández‐Madrigal

Navarro

Asenjo

et al. 2020

Sensors

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Time synchronization among sensor devices connected through non-deterministic media is a fundamental requirement for sensor fusion and other distributed tasks that need a common time reference. In many of the time synchronization methods existing in literature, the estimation of the relation between pairs of clocks is a core concept; moreover, in applications that do not have general connectivity among its devices but a simple pairwise topology, such as embedded systems, mobile robots or home automation, two-clock synchronization is actually the basic form of the time estimation problem. In these kinds of applications, especially for critical ones, not only the quality of the estimation of the relation between two clocks is important, but also the bounds the methods provide for the estimated values, and their computational effort (since many are small systems). In this paper, we characterize, with a thorough parameterization, the possible scenarios where two-clock synchronization is to be solved, and then conduct a rigorous statistical study of both scenarios and methods. The study is based on exhaustive simulations run in a super-computer. Our aim is to provide a sound basis to select the best clock synchronization algorithm depending on the application requirements and characteristics, and also to deduce which ones of these characteristics are most relevant, in general, when solving the problem. For our comparisons we have considered several representative methods for clock synchronization according to a novel taxonomy that we also propose in the paper, and in particular, a few geometrical ones that have special desirable characteristics for the two-clock problem. We illustrate the method selection procedure with practical use-cases of sensory systems where two-clock synchronization is essential.

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An Event-Based Kalman Filter for Clock Synchronization

Cited by 25 publications

References 30 publications

ARS: Adaptive Robust Synchronization for Underground Coal Wireless Internet of Things

ARS: Adaptive Robust Synchronization for Underground Coal Wireless Internet of Things

A Fully Programmable White-Rabbit Node for the SKA Telescope PPS Distribution System

Characterization, Statistical Analysis and Method Selection in the Two-Clocks Synchronization Problem for Pairwise Interconnected Sensors

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