Timing recovery in data storage systems: framework and approach of Kalman filtering
Jin Xie, B. V. K. Vijaya Kumar · International Journal of Product Development · 2008
Recent error correction coding is able to work with low Signal-to-Noise Ratios (SNR), thus increasing the recording densities in data storage systems. With low SNR, conventional timing recovery is likely to lose stability and entire blocks of data may be lost. Reliable timing recovery is required in low SNR to reduce the loss of lock rate. In this paper, we introduce the framework of current timing recovery system, challenges of timing recovery in low SNR, and application of Kalman filtering to timing recovery. With Kalman filtering, timing recovery performance is improved in acquisition, tracking, and dropout compensation, and loss of lock rate is reduced.