Multi-band Moving Object Spectral Detection via Field Segmentation
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Solution Overview
Problem
Current spectral imaging technologies are not suitable for real-time detection and identification of moving objects, fail to track multiple moving objects, and are incapable of online processing and recognition, with high costs and low performance.
Innovation Solution
A method and apparatus that integrate multi-spectral scanners and Fourier transformed infrared imaging spectrometers, dividing the field of view into subfields, calculating object speeds, and selecting modes for tracking and measuring spectra based on speed, with an apparatus comprising a two-dimensional stepping scanning rotating mirror, spectroscope, and multi-band spectrum-measuring units for automatic detection and recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a multi-spectral scanner with Fourier transformed infrared imaging spectrometer is used to integrate image and spectrum detection with one sensor, then abundant two-dimensional space information and third dimensional spectrum data can be obtained, but high spatial resolution and high time resolution cannot be achieved simultaneously and the cost is very high
Solution Approach 1:
The field of view is divided into multiple subfields of view, with each subfield assigned to a separate detector element. This segmentation allows parallel detection of spectral information from multiple spatial locations simultaneously, achieving both high spatial resolution (through multiple subfields) and high time resolution (through parallel detection without sequential scanning).
Solution Approach 2:
The patent transitions from a single-sensor sequential approach to a multi-detector parallel approach by adding the spatial dimension of multiple detectors. Each detector captures spectral data from its assigned subfield simultaneously, converting a time-sequential measurement process into a spatially-parallel process, thereby achieving high temporal resolution while maintaining spatial detail.
2Measurement precision
If conventional spectral imaging apparatus is used for static objects, then multi-spectral remote sensing image information can be obtained through point-by-point scanning, but it is not suitable for real-time detection of moving objects
Solution Approach 1:
By dividing the field of view into multiple subfields and assigning each to a separate detector, the system captures spectral information from multiple locations simultaneously rather than scanning point-by-point. This enables real-time detection of moving objects while maintaining accurate spectral measurement capabilities.
Solution Approach 2:
The multi-detector configuration enables continuous spectral measurement across the entire field of view without the interruptions inherent in sequential scanning. Multiple detectors operate simultaneously and continuously, allowing the system to track and measure spectra of moving objects in real-time without missing data due to scan delays.
3Quantity of substance
If existing spectral imaging apparatus is used for automatic detection and spectrum recognition of moving objects, then spectral data can be collected, but they fail to automatically track and measure the spectrum of multiple moving objects and are incapable of online processing and recognizing object spectrum
Solution Approach 1:
The division of the field of view into multiple subfields, each monitored by a dedicated detector, enables the system to independently track and measure multiple moving objects simultaneously. Each detector can be assigned to track specific objects within its subfield, achieving automatic multi-object tracking and spectral measurement.
Solution Approach 2:
The system performs online processing and recognition of object spectra automatically without requiring external intervention. The detectors continuously capture spectral data, and the integrated system automatically processes and recognizes the spectral information in real-time, enabling self-service automatic detection and identification of moving objects.
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 automatic detection, tracking, and recognition of multiple moving objects' spectra in real-time, achieving online processing and improved performance with flexible and cost-effective multi-band measurement capabilities.
Implementation Method 1
a two-dimensional stepping scanning rotating mirror reflects the objective infrared light to the spectroscope
Implementation Method 2
a spectroscope, a long-wave infrared lens unit, a long-wave infrared imaging unit, a near/short/medium wave infrared lens unit, and a multi-band spectrum-measuring unit
Implementation Method 3
the long wave infrared lens unit focalizes the long wave infrared light, and transmits the long wave infrared light to the long wave infrared imaging unit; the near/short/medium wave infrared lens unit focalizes near/short/medium wave infrared light
Data Source
AI summary
A method for detecting spectral characteristics of multi-band moving objects. The method includes: 1) dividing a full field of view into several subfields of view, and scanning and extracting suspected objects in each subfield one by one; 2) correlating interrelated suspected objects in adjacent subfields via coordinates to determine objects of interest that exist in the full field of view; 3) calculating the speeds of the objects of interest; 4) calculating average speed of all of the objects of interest and classifying the objects of interest according to their average speed; 5) compensating and rectifying the objective spectrum obtained from calculation; and 6) matching the compensated and rectified objective spectrum with a spectrum fingerprint database whereby realizing recognition of the multi-band moving objects.