Digital Filter Spectrum Sensor Resolution Enhancement
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Solution Overview
Problem
The miniaturization of optical spectrometers is hindered by resolution degradation, particularly due to the short distance between the input slit and the detector array, and the limitations of non-dispersion methods using sets of filters with narrow Full Width Half Maximum (FWHM) bandwidths.
Innovation Solution
The implementation of a digital filter spectrum sensor that digitizes and quantizes the spectral responses of a filter array, forming a filter function matrix to estimate the spectral profile using techniques like pseudoinverse operations and least squares methods, enhancing resolution through matrix inversion and noise reduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Volume of moving object
If the distance from the input slit to the detector array is shortened for miniaturization, then the device size is reduced, but the resolution degrades
Solution Approach 1:
The patent replaces the traditional mechanical/optical dispersion system (input slit, dispersive element, detector array requiring long distance) with a filter array system where multiple filters are positioned at different locations. The spectral information is captured through the spatial distribution of light intensities across the filter array, eliminating the need for long optical paths while maintaining resolution capability through mathematical reconstruction techniques.
2Measurement precision
If the number of filters is increased and FWHM is narrowed to improve resolution, then the resolution improves, but the device complexity and cost increase
Solution Approach 1:
The patent changes the approach from using many narrow FWHM filters to using fewer broad bandwidth filters. The resolution is not achieved through filter selectivity alone but through the spatial arrangement of filters and mathematical reconstruction algorithms that analyze the intensity distribution pattern across the filter array, thereby reducing device complexity while maintaining resolution.
Solution Approach 2:
The patent introduces mathematical reconstruction techniques (such as pseudoinverse operations and least squares methods) as an intermediary between the filter array measurements and the final spectral profile. This intermediary processing layer enables high-resolution spectral information to be extracted from measurements obtained with simpler, broad bandwidth filters, avoiding the need for complex narrow bandwidth filters.
3Device complexity
If broad bandwidth filters are used to reduce device complexity, then the device complexity is reduced, but the resolution capability is lost
Solution Approach 1:
The patent transitions from relying on the spectral dimension (narrow FWHM filters) to utilizing the spatial dimension. By arranging broad bandwidth filters at different positions and measuring the intensity distribution across this spatial array, the system captures spectral information through spatial patterns. Mathematical reconstruction techniques then transform this spatial information into high-resolution spectral profiles, effectively adding a spatial dimension to compensate for the loss of spectral selectivity.
Data Source
AI summary
A spectrum sensing method includes (a) receiving an incident radiation simultaneously through a filter array composed of multiple bandpass filters, (b) digitizing spectral responses of the filter array, and (c) generating an estimate of spectral profile of the incident radiation based on digitized spectral responses of the filter array.