Optical System Detecting Scene Inhomogeneity via Field-of-View Modulation
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Solution Overview
Problem
Conventional optical systems fail to accurately analyze scene radiance due to scene inhomogeneity, particularly caused by clouds, leading to analysis errors and noise, as they assume constant radiance and cannot unambiguously determine inhomogeneity within a single field-of-view without requiring observations from multiple adjacent views.
Innovation Solution
An optical system that includes a dichroic mirror and a controller to modulate the field-of-view using sinusoidal, pulse code, or pseudo-random waveforms, allowing for the detection of scene inhomogeneity by processing the amplitude of the radiance signal from a focal plane array, determining homogeneity or inhomogeneity based on signal amplitude relative to noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional optical systems assume constant radiance, then the analysis process is simple, but measurement precision deteriorates due to inability to detect scene inhomogeneity
Solution Approach 1:
The patent applies periodic action by modulating the field-of-view at a known frequency to detect scene inhomogeneity. The controller oscillates the FOV at a predetermined frequency, and the processor analyzes the modulated signal to determine whether the scene is homogeneous or inhomogeneous. This periodic modulation enables the system to distinguish between constant radiance and varying radiance patterns without requiring complex multi-view observations.
Solution Approach 2:
The system implements feedback by continuously monitoring the radiance signal for modulation at the predetermined frequency. The processor feedbacks the analysis results to determine scene homogeneity, which then informs whether to proceed with atmospheric parameter retrieval or adjust the observation strategy. This feedback mechanism improves measurement precision while maintaining manageable system complexity.
2Reliability
If cloud clearing methods are used to remove inhomogeneity, then analysis accuracy may improve, but reliability deteriorates because these methods cannot unambiguously determine inhomogeneity for individual FOVs
Solution Approach 1:
The system applies self-service by enabling each individual field-of-view to self-determine its homogeneity status through the periodic modulation technique. The modulated signal analysis allows each FOV to independently assess whether it contains homogeneous or inhomogeneous radiance patterns, eliminating the need to rely on adjacent FOV observations or external cloud-clearing algorithms. This self-determination provides unambiguous reliability for each measurement.
Solution Approach 2:
The patent utilizes parameter changes by transforming the detection approach from spatial analysis (requiring multiple adjacent FOVs) to temporal analysis (single FOV over time). By changing the parameter domain from spatial homogeneity assessment to temporal signal modulation detection, the system achieves reliable and unambiguous inhomogeneity determination for each individual FOV, thereby improving both reliability and measurement precision simultaneously.
3Measurement precision
If multiple adjacent fields of view are observed to determine inhomogeneity, then measurement precision improves, but loss of time increases due to requiring multiple observations
Solution Approach 1:
The system eliminates time loss by applying periodic action within a single field-of-view observation. The controller oscillates the FOV at a predetermined frequency, and the processor detects the modulation in the radiance signal. This temporal modulation technique allows the system to determine scene inhomogeneity accuracy within a single FOV observation, eliminating the need to sequentially observe multiple adjacent FOVs and thereby reducing observation time while maintaining measurement precision.
Solution Approach 2:
The patent applies preliminary action by pre-modulating the field-of-view at a known frequency before radiance measurement. This preliminary oscillation of the FOV creates a detectable signal pattern that enables immediate identification of scene inhomogeneity during the observation. By preparing the observation setup in advance with the modulation pattern, the system achieves rapid and accurate inhomogeneity detection without requiring subsequent additional observations.
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
This approach enables accurate determination of scene inhomogeneity, reducing analysis errors and noise by distinguishing between homogeneous and inhomogeneous scenes, thereby improving the accuracy of atmospheric parameter retrieval algorithms.
Implementation Method 1
a dichroic mirror for receiving radiance of a field-of-view (FOV) of a scene, and reflecting a portion of the radiance to an optical detector
Implementation Method 2
The optical detector provides a signal of the reflected portion of radiance of the scene
Data Source
AI summary
An optical system measures scene inhomogeneity. The system includes a mirror for receiving radiance of a field-of-view (FOV) of a scene, and reflecting a portion of the radiance to an optical detector. A controller is coupled to the mirror for changing the FOV. The optical detector provides a signal of the reflected portion of radiance of the scene. A processor determines scene inhomogeneity, based on amplitude of the signal provided from the optical detector. The controller is configured to modulate the FOV at a periodic interval, using a sinusoidal waveform, a pulse code modulated waveform, or a pseudo-random waveform.