Signal Interpolation for Jitter Component Separation
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Solution Overview
Problem
Current methods for determining event timings in signals are complex and lack a simple, cost-efficient approach to separate and analyze jitter components, particularly in serial data communications systems where jitter can cause data errors.
Innovation Solution
A signal interpolation method that digitizes an analog input signal, identifies crossings with respect to a threshold, and interpolates between successive samples using linear slopes to generate a waveform that can be processed for jitter component separation, allowing for improved estimation of event timings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Clock Data Recovery (CDR) is used to identify event timings, then timing accuracy is improved, but device complexity increases
Solution Approach 1:
The patent extracts only the essential timing information needed for jitter analysis by using a simplified interpolation method that identifies crossing points between signal portions and threshold, rather than implementing a full CDR system. This extraction approach maintains timing accuracy while reducing complexity by removing unnecessary CDR components.
Solution Approach 2:
The patent creates a simplified model of the signal waveform using linear interpolation between sampled points to estimate crossing times. This copying approach replicates the essential timing characteristics without requiring the complex hardware of a full CDR system, thereby reducing device complexity while preserving measurement precision.
2Measurement precision
If spectrum analysis is used to separate deterministic and random jitter, then jitter component separation is improved, but device complexity increases
Solution Approach 1:
The patent extracts timing information through a simplified interpolation process that directly calculates crossing points from sampled signals. This extraction method separates jitter components by analyzing the interpolated waveform characteristics without requiring full spectrum analysis hardware, thereby maintaining measurement precision while reducing device complexity.
3Measurement precision
If linear interpolation with variable slopes is used to generate interpolated signal, then timing estimation accuracy is improved, but calculation complexity increases
Solution Approach 1:
The patent changes the parameter representation by using variable slopes for the two linear signal portions instead of a single uniform slope. This parameter change allows the interpolated signal to better match the actual waveform characteristics, improving timing estimation accuracy. The slopes are determined by the sample values and threshold position, making the calculation adaptive without requiring complex algorithms.
Data Source
AI summary
A signal interpolation method is described. The method includes: receiving an analog input signal; digitizing the analog input signal received, thereby obtaining a digitized input signal having samples; determining a crossing of the digitized input signal with respect to a threshold that was set; and interpolating a signal between at least two successive samples, wherein the signal interpolated has two signal portions each having a linear slope, and wherein one of the signal portions crosses the threshold. A measurement instrument is also described.