scholarly journals A Pilot Symbols Aided Adaptive Kalman Filter for Joint Carrier Phase and Polarization Tracking in Coherent Optical System

2018 ◽  
Vol 9 (1) ◽  
pp. 27 ◽  
Author(s):  
Juntao Cao ◽  
Yanfu Yang ◽  
Qian Xiang ◽  
Qun Zhang ◽  
Linsheng Fan ◽  
...  

A joint compensation scheme based on pilot symbols aiding adaptive Kalman filter (AKF) for phase noise and polarization cross-talk is proposed and investigated via numerical simulation and experimental demonstration. In the proposed scheme, the optimizing parameter Q is adaptively adjusted according to signal parameters or channel conditions. This improvement avoids the drawback of conventional extended Kalman filter (EKF), and its performance is strongly dependent on Q. Another improvement is that the convergence speed of AKF is improved. Pilot quadrature phase shift keyin (QPSK) symbols are inserted into 16 quadrature amplitude modulation (QAM) signals periodically. Besides accelerating convergence speed, the employment of pilot symbols also improves the tracking capability of AKF. The format ratio between pilot symbols and payload symbols is suggested under different system environments, for instance, optical signal-to-noise rate, polarization rotation frequency drift rate, and laser linewidth. With the proposed scheme, it has excellent tolerance to initial parameter Q and dramatically improves the performances in convergence speed, polarization rotation frequency drift rate tracking, and carrier phase recovery. Both the numerical simulation and experimental demonstration achieve convergence improvement for around 40 times than the original AKF. Additionally, the improvements in tracking ability are also demonstrated.

2010 ◽  
Vol 53 (12) ◽  
pp. 2653-2663 ◽  
Author(s):  
ChenXi Lu ◽  
YunHua Tan ◽  
BoCheng Zhu ◽  
LeZhu Zhou

2013 ◽  
Vol 62 (2) ◽  
pp. 251-265 ◽  
Author(s):  
Piotr J. Serkies ◽  
Krzysztof Szabat

Abstract In the paper issues related to the design of a robust adaptive fuzzy estimator for a drive system with a flexible joint is presented. The proposed estimator ensures variable Kalman gain (based on the Mahalanobis distance) as well as the estimation of the system parameters (based on the fuzzy system). The obtained value of the time constant of the load machine is used to change the values in the system state matrix and to retune the parameters of the state controller. The proposed control structure (fuzzy Kalman filter and adaptive state controller) is investigated in simulation and experimental tests.


Author(s):  
Lifei Zhang ◽  
Shaoping Wang ◽  
Maria Sergeevna Selezneva ◽  
Konstantin Avenirovich Neysipin

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