Sync Mark Detection via Data Detector Branch Metrics
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Solution Overview
Problem
Existing storage systems face challenges in accurately detecting synchronization marks due to noise and inefficiencies in circuit area usage, particularly with Euclidean metric computation modules.
Innovation Solution
The method involves reusing branch metrics from a data detector to generate sync mark metrics, eliminating the need for a dedicated Euclidean metric computation module and improving sync mark detection by comparing input data with sync mark patterns to assert a sync mark found signal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a dedicated Euclidean metric computation module is used to detect sync marks, then detection accuracy can be achieved, but circuit area requirements increase significantly
Solution Approach 1:
The patent merges the sync mark detection function with the existing data detector by reusing its branch metrics computation capability. Instead of implementing a separate Euclidean metric computation module, the invention combines both functions into a single integrated detector that performs both data detection and sync mark detection using shared computational resources.
Solution Approach 2:
The data detector is designed to perform multiple functions: it computes branch metrics for both data detection and sync mark detection. The same computational infrastructure serves dual purposes, making the detector universal and eliminating the need for dedicated hardware for each function.
2Area of stationary object
If branch metrics are reused for sync mark detection, then circuit area is reduced, but detection reliability may be affected by noise
Solution Approach 1:
The invention converts the potential harm of noise interference into a benefit by using the same branch metrics for both data detection and sync mark detection. The noise affects both detections equally, and the correlation between the two functions actually improves overall system reliability through consistent metric evaluation under the same noise conditions.
Solution Approach 2:
The system employs feedback mechanisms where the data detector's branch metrics are fed into the sync mark detection logic. This feedback loop allows the system to continuously evaluate sync mark candidates using the same computational path, improving reliability through consistent metric evaluation and noise cancellation techniques.
Data Source
AI summary
Methods and apparatus are provided for detecting a sync mark in a storage system, such as a hard disk drive. A sync mark is detected in a storage system by obtaining one or more branch metrics from a data detector in the storage system; generating one or more sync mark metrics using the one or more branch metrics from the data detector; and identifying the sync mark based on the sync mark metrics. An input data set is optionally compared with a plurality of portions of a sync mark pattern to yield corresponding comparison values and the comparison values can be summed to obtain at least one result. A sync mark found signal is asserted based upon the at least one result.


