Spectral Band Selection for Hyperspectral Sensor Configuration
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Solution Overview
Problem
Mobile surveillance platforms face challenges in accurately configuring sensors to collect spectral data from geographic areas due to unknown target and background characteristics, leading to increased processing and communication burdens, especially with hyperspectral imaging.
Innovation Solution
A system and method for simulating spectral information of a region of interest by generating a simulated spectral representation using GIS data and spectral libraries, allowing for intelligent configuration of sensors to collect and process desired geospatial data, including identifying materials of interest and background materials, and selecting optimal spectral bands for data collection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If hyperspectral imagers are used to collect detailed spectral information, then measurement precision and information quality are improved, but processing requirements and device complexity increase severely
Solution Approach 1:
The patent extracts only the essential spectral bands needed for identifying materials of interest from the full hyperspectral spectrum. By selecting a subset of bands (e.g., 5-10 bands out of 100+ available), the system maintains measurement precision for target identification while dramatically reducing processing requirements and data transmission loads.
Solution Approach 2:
The patent applies local quality by configuring different spectral band selections for different regions of interest. Instead of uniformly processing all hyperspectral data, the system identifies specific bands that are most relevant for detecting particular materials in specific geographic areas, optimizing processing efficiency while maintaining detection accuracy.
2Adaptability or versatility
If hyperspectral sensing is used to ease spectral band planning, then adaptability is improved, but sensor resolution requirements and update frequency concerns are worsened
Solution Approach 1:
The patent performs preliminary action by pre-identifying the optimal spectral bands for detecting specific materials before actual data collection. Using simulated spectral representations and material databases, the system determines which bands will be most effective for identifying targets of interest, allowing sensor configuration to be optimized in advance rather than requiring real-time high-resolution adjustments.
3Measurement precision
If sensor characteristics are chosen to maximize discriminants between target and background, then measurement precision is improved, but device complexity increases when target characteristics are unknown
Solution Approach 1:
The patent performs preliminary action by pre-configuring sensor characteristics based on simulated spectral representations of expected targets and backgrounds. Before deployment, the system models the spectral signatures of potential materials of interest and background materials, then selects sensor bands and characteristics that will maximize discrimination capability, eliminating the need for complex real-time adjustments when targets are unknown.
Solution Approach 2:
The patent uses simulated spectral representations as copies of actual target and background materials. By creating virtual models of spectral signatures from databases and simulations, the system can optimize sensor configuration without requiring physical samples or prior knowledge of actual targets, reducing complexity while maintaining measurement precision.
Data Source
AI summary
A system and method for collecting spectral data of a region of interest with a sensor is described. In one embodiment, the method comprises generating a simulated spectral representation of a region of interest, identifying at least one of the plurality of materials as a material of interest within the region of interest, identifying other of the plurality of materials not identified as a material of interest as background materials within the region of interest, selecting a subset spectral portion of the spectral data according to the simulated spectral representation of the material of interest and the simulated spectral representation of the background materials within the region of interest, and configuring the sensor to collect a subset spectral portion of the spectral data.