Dual-Channel Optical Interference Signal Separation
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Solution Overview
Problem
In dual-channel laser wavenumber scanning three-dimensional Michelson-type interference systems, the underdetermined blind source separation challenge arises when the number of observed signals is smaller than the number of source signals, leading to difficulties in separating interference signals due to noise fluctuations and overlapping signals.
Innovation Solution
A dual-channel optical three-dimensional interference method is developed, utilizing a Michelson-type interferometer with independent reference and measurement light paths, incorporating a liquid crystal chip to suppress reference light intensity, and employing linear frequency modulation, Fourier transforms, fast Fourier transforms, K-means clustering, and L1 norm minimum path algorithms to separate source signals in the frequency domain.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the number of observed signals is smaller than the number of source signals, then the system complexity is reduced, but the source signals cannot be obtained in a form of an inverse matrix and signal separation becomes difficult
Solution Approach 1:
The patent transforms the signal processing from time domain to frequency domain by applying Fourier transform. This parameter change in the domain of signal representation enables the separation of underdetermined source signals, as the frequency domain provides a different perspective where the mixing matrix becomes more amenable to inversion through clustering techniques.
Solution Approach 2:
The patent replaces traditional mechanical signal separation methods with computational intelligence approaches, specifically K-means clustering and L1 norm minimization algorithms. This substitution allows for the separation of underdetermined source signals by using mathematical optimization rather than direct matrix inversion, solving the fundamental problem of having fewer observed signals than source signals.
2Measurement precision
If noise fluctuation is too strong while an amplitude of an interference signal is relatively small, then the measurement sensitivity is improved, but two considerably close interference signals overlap into one signal
Solution Approach 1:
The patent replaces traditional signal filtering methods with intelligent signal processing algorithms including K-means clustering and L1 norm minimization. These computational methods can distinguish between overlapping interference signals by exploiting their different statistical properties and sparsity patterns in the frequency domain, even when noise levels are high and signal amplitudes are small.
Solution Approach 2:
The patent moves signal processing from the time domain to the frequency domain, adding a dimensional transformation that provides better separation between overlapping signals. In the frequency domain, signals that are mixed in time can be distinguished by their different frequency characteristics, enabling reliable signal separation even under noisy conditions.
3Measurement precision
If a liquid crystal chip is introduced to suppress reference light intensity, then the interference signal quality is improved, but the device complexity increases
Solution Approach 1:
The patent introduces a liquid crystal chip as an intermediary element in the reference light path. This intermediary component dynamically controls the reference light intensity, allowing for optimization of the interference signal quality by adjusting the balance between reference and measurement light paths, thereby improving signal-to-noise ratio and interference contrast.
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
This method effectively separates source signals even under strong noise conditions, improving depth profile resolution and reducing phase fluctuation errors, enabling accurate detection of interference signal positions and amplitude-frequency characteristics.
Implementation Method 1
performing linear frequency modulation on a wavenumber output of a semiconductor laser through a laser controller and a temperature control module
Implementation Method 2
splitting the parallel light into two beams of light by a beam splitter of a 50:50 cube
Implementation Method 3
provides a liquid crystal chip in the interference reference light path, thereby suppressing a light intensity of reference light
Implementation Method 4
collimating, by a first lens, laser output light into parallel light; concentrating, by a second lens, the return light path
Implementation Method 5
dual-channel laser wavenumber scanning three-dimensional Michelson-type interference; superimposing return light paths on each other in the data acquisition card to form an interference signal
Implementation Method 6
performing fast Fourier transform (FFT) performed on the signal for transformation to the frequency-domain to form a sparse signal
Implementation Method 7
employing linear frequency modulation, Fourier transforms, fast Fourier transforms, K-means clustering, and L1 norm minimum path algorithms to separate source signals in the frequency domain
Data Source
AI summary
The present disclosure discloses a dual-channel optical three-dimensional interference method based on underdetermined blind source separation, which blindly separates out, through interference data collected by a CCD camera, interference signals between surfaces of a slide under test, to solve interference signal parameters, including an interference signal amplitude-frequency and an interference signal phase-frequency. Based on a dual-channel optical three-dimensional Michelson-type interference experiment, estimation of a mixed matrix is obtained by a K-means clustering algorithm, and recovery of a source signal is achieved by a L1 norm shortest path method. It is finally achieved that laser wavenumber scanning can accurately and blindly separate out the interference signals of the four surfaces based on light intensity values collected by the CCD camera, to achieve the blind separation of the interference signals of the four surfaces.