Infrared Spectrum Dictionary for Real-Time Remote Target Detection
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Solution Overview
Problem
Existing spectrometers are not suitable for real-time acquisition of spectra from distant moving targets and dynamic phenomena due to structural complexity, high computation load, and limited detection distance, especially in complex environments with low signal-to-clutter and signal-to-noise ratios.
Innovation Solution
A method and system that build a short-wave, medium-wave, and long-wave infrared spectrum dictionary by normalizing and performing weighted combinations on infrared spectrum response curves from a three-primary-color sensor group, creating an image-space infrared spectrum dictionary through multi-scale discretization and clustering, and combining it with object-space Planck curves to support real-time computational spectrometry imaging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a conventional spectroscopic imaging spectrometer is used to split the beam finer, then the spectral resolution is improved, but the detection distance is reduced
Solution Approach 1:
The patent introduces an intermediary computational spectrometry system that mediates between the sensor array and spectral analysis. By using a computational approach with a spectrum dictionary built from Planck curves and chromaticity diagrams, the system achieves high spectral resolution without requiring fine beam splitting, thus maintaining long detection distance.
2Length of stationary object
If a Fourier interference imaging spectrometer is used to increase luminous flux, then the detection distance is improved, but the structure becomes complex and computation load increases
Solution Approach 1:
The patent extracts the complex Fourier interference imaging components and replaces them with a simpler computational spectrometry approach. By taking out the need for complex optical structures and using instead a dictionary-based computational method with Pre-computed Planck curves and chromaticity diagrams, the system achieves long detection distance with reduced structural and computational complexity.
Solution Approach 2:
The patent creates a computational copy of the spectral analysis function through the spectrum dictionary. Instead of using complex optical instruments to physically separate and analyze spectra, the system creates a digital representation (copy) of spectral characteristics through the dictionary built from Planck curves, enabling spectral analysis with simpler hardware.
3Productivity
If conventional imaging spectrometers are used for real-time spectrum acquisition, then the spectral cube can be obtained, but the computation load is heavy and real-time processing is difficult
Solution Approach 1:
The patent performs preliminary action by pre-computing and storing Planck curves for various temperatures and chromaticity diagram data in the spectrum dictionary before actual measurement. This preliminary preparation eliminates the need for heavy real-time computations, enabling fast spectral analysis by simply looking up pre-computed values in the dictionary during real-time operation.
Solution Approach 2:
The patent replaces expensive, complex real-time computational spectrometry with a simpler, more efficient dictionary lookup approach. By using pre-computed spectral data that can be quickly retrieved and matched, the system achieves real-time performance without the heavy computation burden of conventional methods.
4Measurement precision
If spectral video imaging or snapshot with aperture coding is used, then the spectral band is narrowed, but the broadband detection capability is reduced
Solution Approach 1:
The patent achieves universality by building a comprehensive spectrum dictionary that covers the entire infrared spectrum (short-wave, medium-wave, and long-wave bands) using Planck curves and chromaticity diagrams. This universal dictionary enables the system to detect and analyze spectra across all infrared bands simultaneously, providing both spectral precision and broadband detection capability.
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
Enables real-time acquisition of spectra from remote moving targets and dynamic phenomena by adapting to complex environments with improved signal processing and spectral analysis, enhancing the detection and identification capabilities in infrared imaging.
Implementation Method 1
measuring to obtain infrared spectrum response curves of an infrared three-primary-color sensor group
Implementation Method 2
performing normalization on the infrared spectrum response curves of the infrared three-primary-color sensor group, using same as spectrum-based functions, and taking the proportions of the sum of tristimulus values accounted for by the tristimulus values corresponding to an infrared imaging sensor group as chromaticity
Implementation Method 3
performing weighted combination on the infrared spectrum response curves to build an initial image-space infrared spectrum dictionary
Implementation Method 4
performing multi-scale discretization on the infrared three-primary-color chromaticity diagram, clustering chromaticity coordinates generated by discretization into different groups
Implementation Method 5
performing weighted combination on object-space Planck curves associated with three different temperatures to build an object-space Planck spectrum dictionary
Data Source
AI summary
A method and a system for building a short-wave, medium-wave and long-wave infrared spectrum dictionary are provided. The method includes: building an infrared three-primary-color chromaticity diagram by using infrared spectrum response curves of an infrared three-primary-color sensor group; performing weighted combination on the infrared spectrum response curves; performing multi-scale discretization on the infrared three-primary-color chromaticity diagram, clustering chromaticity coordinates generated by discretization into different groups, performing weighted combination on the infrared spectrum response curves corresponding to the chromaticity coordinates of each point in the groups, generating a new image-space infrared spectrum, and adding the new image-space infrared spectrum to an initial image-space infrared spectrum dictionary; performing weighted combination on object-space Planck curves associated with three different temperatures to build an object-space Planck spectrum dictionary; and using the final image-space infrared spectrum dictionary and the object-space Planck spectrum dictionary to build the short-wave, medium-wave and long-wave infrared spectrum dictionary.