Temporal-Spectral Multiplexing Sensor for Artifact-Free Spectral Signatures
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Solution Overview
Problem
Spectral sensors face challenges in accurately detecting temporal and spectral signatures due to artifacts from intensity fluctuations, which distort the apparent spectrum and interfere with high-fidelity temporal analysis.
Innovation Solution
A temporal-spectral multiplexing sensor that integrates Hypertemporal Imaging (HTI) and Hyperspectral Imaging (HSI) using data encoding and signal processing to recover temporal signals without HSI encoding artifacts and to normalize spectrally encoded images, reducing or removing intensity-related distortions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If spectral encoding is performed using Hadamard transform with SLM, then spectral resolution is improved, but temporal artifacts are introduced due to intensity fluctuations
Solution Approach 1:
The patent segments the spectral encoding process into multiple sequential measurements, where each measurement captures a different spectral component. By dividing the full spectral range into multiple bands and measuring them separately, the system achieves high spectral resolution while the temporal coherence within each short measurement window minimizes artifacts from intensity fluctuations.
Solution Approach 2:
The patent employs periodic modulation of the spectral components using the SLM, cycling through different spectral band combinations in a systematic sequence. This periodic action allows the system to encode spectral information temporally while maintaining synchronization that enables artifact removal through coherent integration of the periodic measurements.
2Measurement precision
If sequential spectral band passes are used for encoding, then spectral signature accuracy is improved, but detection time is increased
Solution Approach 1:
The patent merges multiple sequential spectral measurements into a single integrated spectral signature through coherent integration. By combining the information from multiple band-pass measurements using the Hadamard transform decoding, the system reconstructs the complete spectral signature faster than sequential scanning would allow, reducing detection time while maintaining accuracy.
Solution Approach 2:
The patent performs preliminary encoding of multiple spectral components simultaneously using the SLM before detection. The SLM pre-configures the optical path to encode multiple spectral bands in a coordinated manner, allowing the detector to capture integrated information that would otherwise require sequential measurement, thereby reducing detection time.
3Measurement precision
If intensity normalization is applied to remove artifacts, then spectral fidelity is improved, but processing complexity is increased
Solution Approach 1:
The patent implements feedback-based normalization where the detected intensity fluctuations are measured and used to correct the spectral encoding. The system monitors the overall intensity signal and uses this feedback to normalize the spectrally encoded measurements, removing artifacts while maintaining spectral fidelity through an automated correction process.
Solution Approach 2:
The patent introduces an intermediary normalization step that mediates between the raw spectral encoding and the final spectral signature. This intermediary process separates the artifact removal function from the spectral encoding function, allowing each to be optimized independently while working together to achieve high spectral fidelity with manageable processing complexity.
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
The sensor achieves enhanced detection and reduced clutter by simultaneously processing HTI and HSI data streams, enabling high-fidelity spectral signature capture from transient events and unstable sources, improving detection capabilities by several orders of magnitude compared to traditional methods.
Implementation Method 1
the SLM provides the ability to spectrally encode the image by applying a pattern which binary-modulates the spectral content of each spatial element of the SLM
Implementation Method 2
a first optical path that produces a spectrally dispersed image of the input radiation field comprising multiple spectral components displaced along a dispersion direction
Implementation Method 3
The detector produces an electrical signal as a temporal function of the detected light intensity
Implementation Method 4
A digital signal processor converts the digital signal into a function of frequency using Fourier transform and power spectral density (PSD)
Implementation Method 5
which senses the intensity of time varying signals, from flickering sources, or from scattered light reflected by a vibrating surface
Data Source
AI summary
A temporal-spectral multiplexing sensor for simultaneous or near simultaneous spatial-temporal-spectral analysis of an incoming optical radiation field. A spectral encoder produces a time series of spectrally encoded optical images at a high sampling rate. A series of full panchromatic spectrally encoded optical images are collected at a rate similar to the sampling rate. A detector records at least one spatial region of the spectrally encoded optical image. A processor is configured to process two series of spectrally encoded optical images to produce an artifact-free spectral image. The processing includes using the panchromatic images to normalize the spectrally encoded images, and decoding the normalized encoded images to produce high fidelity spectral signatures, free of temporal artifacts due to fluctuations at frequencies slower than the sampling rate for polychromatic images.