Sliding-Window Phase Gain DC Offset Estimation
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Solution Overview
Problem
Existing data processing systems for magnetic storage devices face challenges with timing, gain, and DC recovery due to real-time interaction between digital and analog circuits, leading to propagation delays and underutilization of preamble data after discrete Fourier transform integration.
Innovation Solution
A method and system that perform zero phase start, zero gain start, and zero offset start calculations over sliding windows, averaging these values to determine final phase, gain, and DC estimates, eliminating the need for real-time analog circuit updates and minimizing performance degradation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If real-time interaction between digital and analog circuits is implemented for timing, gain and DC recovery, then the estimates can be updated in real-time, but propagation delay occurs in the signal path
Solution Approach 1:
The patent performs timing, gain, and DC recovery estimates using discrete Fourier transform on the entire servo preamble before the main data processing. By completing these estimates in advance during the preamble period and storing them for later use, the system eliminates the need for real-time analog circuit updates during data processing, thereby removing propagation delays while maintaining the benefits of having these parameters optimized.
2Measurement precision
If discrete Fourier transform integration window is used, then phase, gain and DC error estimates can be obtained, but the preamble data after the integration window is not utilized
Solution Approach 1:
The patent applies discrete Fourier transform at multiple overlapping windows across the entire servo preamble, not just a single integration window. By continuously sliding the analysis window across all available preamble data and accumulating the estimates from each window, the system fully utilizes every portion of the preamble signal, thereby extracting maximum information without wasting any preamble data while maintaining or improving estimate accuracy through averaging.
Data Source
AI summary
Sliding-window based data processing includes receiving an analog signal, converting the analog signal to a series of digital samples synchronous to a sampling clock, performing a first discrete Fourier transform on a first portion of the series of digital samples, performing a second discrete Fourier transform on a second portion of the series of digital samples, performing a third discrete Fourier transform on a third portion of the series of digital samples, generating a first series of zero phase start values by calculating a zero phase start value based on the first discrete Fourier transform in a sliding-window at a series of time increments across the servo preamble, storing the zero phase start values, and averaging the stored zero phase start values at the end of the servo preamble.