Jittered Signal Sampling for Detecting Frequencies Beyond Nyquist
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Solution Overview
Problem
Existing systems face challenges in detecting frequency components outside the Nyquist frequency range due to aliasing effects, leading to undetectable signals and reduced system robustness and performance.
Innovation Solution
A converter system exploits random jitter and noise using existing hardware to sample signals, employing a discrete Fourier transform (DFT) to compute sample averages, allowing detection of target frequencies beyond the Nyquist limit by injecting offset sampling times with random jitter.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If systems use traditional sampling methods within the Nyquist frequency range, then aliasing is suppressed and signal accuracy is maintained, but frequency components outside the detectable range cannot be detected
Solution Approach 1:
The patent changes the sampling frequency parameter dynamically by applying random jitter to the sampling clock, allowing the system to detect frequency components beyond the traditional Nyquist limit. The random jitter modifies the effective sampling rate for each sample, enabling detection of higher frequency components through spectral spreading and correlation techniques.
2Adaptability or versatility
If systems extend the detectable frequency range beyond Nyquist, then more frequency components can be detected, but aliasing effects increase and interfere with signal accuracy
Solution Approach 1:
The patent converts the harmful aliasing effect into a beneficial measurement mechanism. By intentionally introducing random jitter that causes controlled aliasing, the system creates a unique spectral signature for each frequency component. The correlation between the jitter pattern and the aliased components allows accurate recovery of the original frequency, transforming aliasing from a distortion source into a detection mechanism.
3Measurement precision
If systems use tailored circuitry to suppress aliasing, then signal accuracy is improved, but device complexity and costs increase
Solution Approach 1:
The patent replaces complex hardware aliasing suppression circuitry with a software-based signal processing approach. Instead of using additional analog filters or specialized circuits to prevent aliasing, the system uses digital correlation processing to recover frequency information from aliased samples, substituting mechanical/electrical complexity with computational complexity.
4Adaptability or versatility
If systems sample at higher frequencies to detect higher frequency components, then detectable frequency range is extended, but sampling rate requirements and processing load increase
Solution Approach 1:
The patent applies partial sampling by using random jitter to selectively sample at varying rates rather than continuously at maximum frequency. The random jitter introduces sufficient variation to capture high-frequency components through correlation, but does not require the full processing power of a uniformly high-rate sampling system, achieving efficient partial observation of the signal spectrum.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively detects and extracts information from target frequencies outside the detectable range, improving system robustness and performance by avoiding hardware modifications and aliasing interference.
Implementation Method 1
the sampling times having an offset associated with random jitter and the target frequency is outside a detectable range for the sampling times
Implementation Method 2
compute a sample average associated with the sampling times for component frequencies of the signal using a DFT
Data Source
AI summary
System, methods, and other embodiments described herein relate to sampling signals to derive information from a target frequency outside a detectable range by exploiting physical phenomena. In one embodiment, a method includes sampling, by a detector with an oscillator, a signal at sampling times to acquire a target frequency, the sampling times having an offset associated with random jitter and the target frequency is outside a detectable range for the sampling times. The method also includes computing a sample average associated with the sampling times for component frequencies of the signal using a discrete Fourier transform (DFT). The method also includes, in response to the sample average satisfying a threshold for the target frequency, extracting information by the detector for the target frequency at one of the component frequencies. The method also includes modifying control of a device using the information.