High Precision Clock Bias Prediction Model in Clock Synchronization System

Zan Liu,Jin Liu,Chenglong Li,Xihong Chen

doi:10.1155/2016/1813403

Abstract

Time synchronization is a fundamental requirement for many services provided by a distributed system. Clock calibration through the time signal is the usual way to realize the synchronization among the clocks used in the distributed system. The interference to time signal transmission or equipment failures may bring about failure to synchronize the time. To solve this problem, a clock bias prediction module is paralleled in the clock calibration system. And for improving the precision of clock bias prediction, the first-order grey model with one variable (GM(1,1)) model is proposed. In the traditional GM(1,1) model, the combination of parameters determined by least squares criterion is not optimal; therefore, the particle swarm optimization (PSO) is used to optimize GM(1,1) model. At the same time, in order to avoid PSO getting stuck at local optimization and improve its efficiency, the mechanisms that double subgroups and nonlinear decreasing inertia weight are proposed. In order to test the precision of the improved model, we design clock calibration experiments, where time signal is transferred via radio and wired channel, respectively. The improved model is built on the basis of clock bias acquired in the experiments. The results show that the improved model is superior to other models both in precision and in stability. The precision of improved model increased by 66.4%~76.7%.

Highlights

Time synchronization technology has been widely used in the distributed system [1,2,3,4], such as global navigation satellite system (GNSS) and multistatic radar and electric network
The way to calibrate local clock is that finite impulse response (FIR) filter uses the bias between local and remote clock measured by time interval counter (TIC) or discriminator to get a control signal [8,9,10], which is used to regulate clock until the clocks are synchronized
When a channel interruption or equipment failure happens, the bias predicted by GM(1, 1) model improved by improved particle swarm optimization (IPSO) can be used to produce the control signal, which is used to synchronize the clock

Summary

Introduction

Time synchronization technology has been widely used in the distributed system [1,2,3,4], such as global navigation satellite system (GNSS) and multistatic radar and electric network. Clock calibration is that devices of distributed system use reference time to synchronize the local clock. In order to guarantee the distributed system work normally and add anti-interference ability of the synchronization system, clock bias prediction module is paralleled in the clock calibration system. In this parallel module, clock bias could be acquired through the prediction module, when the system cannot get clock bias. Parameters of GM(1, 1) model are usually determined by the least square criterion (LSC), which cannot guarantee the parameters are optimal Aiming at this problem, we introduce the particle swarm optimization (PSO) algorithm to optimize GM(1, 1) model.

Clock Bias Prediction in Clock Calibration

PPS 1 PPS

Example Analysis

Conclusion