Distributed Nodes-Based Collaborative Sustaining of Precision Clock Synchronization upon Master Clock Failure in IEEE 1588 System

Son, Kyou Jung; Chang, Tae‐Gyu

doi:10.3390/s20205784

Cited by 7 publications

(6 citation statements)

References 20 publications

(14 reference statements)

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“…In addition, the system is sensitive to the outliers in the measured and predicted values [33]. When the outliers occur, the innovation will increase sharply, and then a large fade factor and abnormal prediction correction value will be calculated, which will lead to a sharp increase in the Kalman gain according to (5), and finally a very large clock fluctuation will occur. In order to solve the above problems, this paper proposes a new strong tracking algorithm based on fuzzy logic and hypothesis testing, as follows:…”

Section: Modified Strong Tracking Algorithmmentioning

confidence: 99%

“…Then, ( 17) is used to obtain the final modified P(k). Next, the state estimates X (k ) and P (k ) are obtained by (5). Finally, X (k ) is used in the form of frequency compensation to control the slave clock, thus completing a synchronization cycle.…”

Section: Overall Structure Of Proposed Mstakf Algorithmmentioning

confidence: 99%

“…If the clock offset is directly compensated, the time fluctuation will be caused. Moreover, according to research [5][6][7], if there is clock drift at the slave clock side, this drift is ideally proportional to the amount of frequency drift. In addition to the fixed frequency drift, there are actually random drifts affected by temperature, communication networks, and other interferences, both of which can also cause clock drift.…”

Section: Introductionmentioning

confidence: 99%

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A Modified Strong Tracking Adaptive Kalman Filter for Precision Clock Synchronization System

Zhang,

Hou

2023

IEEJ Transactions Elec Engng

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In order to reduce the clock offset caused by network delay jitter, network asymmetry, clock drift and clock frequency difference in the clock synchronization process of IEEE1588, a modified Strong Tracking Adaptive Kalman Filter (MSTAKF) algorithm was proposed. The Kalman filter model established by the algorithm is based on clock offset, network delay, frequency deviation and asymmetry ratio. The filter includes the modified strong tracking algorithm based on fuzzy logic and hypothesis test proposed in this paper, which can effectively eliminate the influence of outliers, and finally make the model tracking effect better. In addition, the modified Sage‐Husa algorithm based on Cholesky decomposition is also included, which makes the measurement noise more stable and ensures the positivity of the measurement noise covariance. The experimental results show that the proposed MSTAKF is smoother than Karman filter (KF), Sage‐Husa adaptive Kalman filter (AKF) and strong tracking Sage‐Husa adaptive Kalman filter (STAKF). Compared with these filter algorithms after testing in the LAN environment, the precision improvement and accuracy rate are significantly improved. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

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Section: Modified Strong Tracking Algorithmmentioning

confidence: 99%

Section: Overall Structure Of Proposed Mstakf Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Modified Strong Tracking Adaptive Kalman Filter for Precision Clock Synchronization System

Zhang,

Hou

2023

IEEJ Transactions Elec Engng

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“…This varying speed is attributed to the oscillator noise, which varies with the supply voltage, age, temperature, and other environmental factors, resulting in a time-varying skew with certain randomness. In general, the oscillator noise is characterized as a nonstationary process; however, the influential parameters' range of change, such as temperature and humidity, varies relatively slowly with time, resulting in a quasi-stationary process [23,32]. Therefore, it is of utmost importance to keep track of the quasi-stationarity behavior when modeling the clock skew.…”

Section: A Clock Skewmentioning

confidence: 99%

Aerial Vehicles Tracking Using Noncoherent Crowdsourced Wireless Networks

Sallouha

Chiumento

Pollin

2021

IEEE Trans. Veh. Technol.

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Air traffic management (ATM) of manned and unmanned aerial vehicles (AVs) relies critically on ubiquitous location tracking. While technologies exist for AVs to broadcast their location periodically and for airports to track and detect AVs, methods to verify the broadcast locations and complement the ATM coverage are urgently needed, addressing anti-spoofing and safe coexistence concerns. In this work, we propose an ATM solution by exploiting noncoherent crowdsourced wireless networks (CWNs) and correcting the inherent clock-synchronization problems present in such non-coordinated sensor networks. While CWNs can provide a great number of measurements for ubiquitous ATM, these are normally obtained from unsynchronized sensors. This article first presents an analysis of the effects of lack of clock synchronization in ATM with CWN and provides solutions based on the presence of few trustworthy sensors in a large non-coordinated network. Secondly, autoregressivebased and long short-term memory (LSTM)-based approaches are investigated to achieve the time synchronization needed for localization of the AVs. Finally, a combination of a multilateration (MLAT) method and a Kalman filter is employed to provide an anti-spoofing tracking solution for AVs. We demonstrate the performance advantages of our framework through a dataset collected by a real-world CWN. Our results show that the proposed framework achieves localization accuracy comparable to that acquired using only GPS-synchronized sensors and outperforms the localization accuracy obtained based on state-of-the-art CWN synchronization methods.

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“…Wang, Qi, and Li (2020) introduced proportional integral derivative (PID) control in the time synchronization process to reduce the interference error, but it could not adapt to the clock jump caused by fast time variation. Son and Chang (2020) proposed a clock synchronization method based on the precision time protocol (PTP) to estimate the information of the faulty node by collecting and analyzing the clock information of other nodes, but this method does not take into consideration the factor of packet loss, thus leading to inaccurate estimates. Shivaaraman, Schuster, Ramanathan, Easwaran, and Steinhorst (2021) proposed a cluster-based time synchronization protocol, but this method cannot reduce the synchronization error caused by packet loss.…”

Section: Introductionmentioning

confidence: 99%

MPC-based time synchronization method for V2V (vehicle-to-vehicle) communication

Chen

Zhan

Zhang

2023

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PurposeAs the strategy of 5G new infrastructure is deployed and advanced, 5G-R becomes the primary technical system for future mobile communication of China’s railway. V2V communication is also an important application scenario of 5G communication systems on high-speed railways, so time synchronization between vehicles is critical for train control systems to be real-time and safe. How to improve the time synchronization performance in V2V communication is crucial to ensure the operational safety and efficiency of high-speed railways.Design/methodology/approachThis paper proposed a time synchronization method based on model predictive control (MPC) for V2V communication. Firstly, a synchronous clock for V2V communication was modeled based on the fifth generation mobile communication-railway (5G-R) system. Secondly, an observation equation was introduced according to the phase and frequency offsets between synchronous clocks of two adjacent vehicles to construct an MPC-based space model of clock states of the adjacent vehicles. Finally, the optimal clock offset was solved through multistep prediction, rolling optimization and other control methods, and time synchronization in different V2V communication scenarios based on the 5G-R system was realized through negative feedback correction.FindingsThe results of simulation tests conducted with and without a repeater, respectively, show that the proposed method can realize time synchronization of V2V communication in both scenarios. Compared with other methods, the proposed method has faster convergence speed and higher synchronization precision regardless of whether there is a repeater or not.Originality/valueThis paper proposed an MPC-based time synchronization method for V2V communication under 5G-R. Through the construction of MPC controllers for clocks of adjacent vehicles, time synchronization was realized for V2V communication under 5G-R by using control means such as multistep prediction, rolling optimization, and feedback correction. In view of the problems of low synchronization precision and slow convergence speed caused by packet loss with existing synchronization methods, the observer equation was introduced to estimate the clock state of the adjacent vehicles in case of packet loss, which reduces the impact of clock error caused by packet loss in the synchronization process and improves the synchronization precision of V2V communication. The research results provide some theoretical references for V2V synchronous wireless communication under 5G-R technology.

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Distributed Nodes-Based Collaborative Sustaining of Precision Clock Synchronization upon Master Clock Failure in IEEE 1588 System

Cited by 7 publications

References 20 publications

A Modified Strong Tracking Adaptive Kalman Filter for Precision Clock Synchronization System

A Modified Strong Tracking Adaptive Kalman Filter for Precision Clock Synchronization System

Aerial Vehicles Tracking Using Noncoherent Crowdsourced Wireless Networks

MPC-based time synchronization method for V2V (vehicle-to-vehicle) communication

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