Time Acquisition Apparatus Noise Resilient Correlation Detection
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Solution Overview
Problem
Conventional time acquisition apparatuses for standard time radio waves face challenges in accurately extracting time codes due to variations in electric field intensity and noise, leading to frequent reinitialization and prolonged time acquisition processes.
Innovation Solution
A time acquisition apparatus that includes a receiving member, a waveform data obtaining member, a prediction code data generating member, a correlation value calculating member, and a code determining member to compare received waveform data with prediction code data, calculating correlation values to accurately identify and store time codes, thereby reducing noise influence and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional processing circuits use rising edge synchronization and binarization to extract time codes from standard time radio waves, then the processing can be completed through standard demodulation steps, but the acquisition time becomes seriously long due to frequent reinitialization caused by noise
Solution Approach 1:
The patent applies preliminary action by generating prediction code data before comparing with received waveform data. The prediction code data is created based on expected time code patterns, allowing the system to anticipate and quickly identify valid time codes without waiting for complete demodulation and processing of the entire signal frame. This preliminary preparation enables faster synchronization and reduces the time spent on noise filtering and reinitialization.
Solution Approach 2:
The patent replaces the conventional mechanical-style step-by-step demodulation and binarization process with a correlation-based signal processing approach. Instead of sequentially processing through envelope detection, binarization, and bit synchronization, the system uses correlation between prediction code data and received waveform data to directly identify time codes, substituting the mechanical processing chain with a more efficient mathematical correlation method that is more resilient to noise.
2Measurement precision
If the processing circuit starts processing from the beginning when noise is detected, then accurate time code extraction can be attempted, but the frequent reinitialization significantly extends the time acquisition process
Solution Approach 1:
The patent implements feedback by using correlation results to determine whether reinitialization is necessary. The correlation value comparing prediction code data with received waveform data provides feedback on signal quality and synchronization status. When correlation exceeds a threshold, the system confirms accurate detection without reinitialization; when it falls below, targeted reinitialization occurs. This feedback mechanism prevents unnecessary reinitialization events, maintaining detection accuracy while significantly improving acquisition efficiency.
3Ease of operation
If conventional methods binarize the demodulated signal with predetermined sampling period, then the processing can proceed through standard steps, but noise in the signal causes frequent reinitialization and prolongs acquisition time
Solution Approach 1:
The patent applies parameter changes by transitioning from fixed binarization thresholds and sampling periods to dynamic correlation-based parameter adjustment. The system changes the processing parameter from static binarization levels to adaptive correlation thresholds that adjust based on signal characteristics. This parameter transformation maintains processing simplicity through standardized correlation operations while dramatically improving reliability by making the processing stable against noise variations and electric field intensity changes.
Data Source
AI summary
A received waveform memory 22 stores one (1) frame of received waveform data acquired by sampling a signal including a time code with a predetermined sampling period, where each sample is represented by a plurality of bits. Correlation value calculating sections 24-26 compare the received waveform data with one (1) frame of first prediction code data corresponding to a code of a position marker or a marker, where each sample is represented by a plurality of bits, one (1) frame of second prediction code data corresponding to a code “0”, and one (1) frame of third prediction code data corresponding to a code “1” respectively. Correlation value comparing section 27 compares the first, second and third correlation values with one another to specify the prediction code data whose correlation is largest to output the code data.