Optical Compressive Sensing With Spatial Filtering for Sparse Detection
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Solution Overview
Problem
Traditional active remote sensing systems require large size, weight, and power (SWaP) due to linear scaling of optical energy with covered area, leading to high costs and inefficiencies.
Innovation Solution
The implementation of active optical compressive sensing techniques, which involve generating sparse scattered data using spatial filtering patterns, allowing for logarithmic resource scaling and significant reduction in transmitter requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional active remote sensing systems use linear scaling of optical energy with covered area, then measurement precision is maintained, but use of energy increases linearly with area
Solution Approach 1:
The patent segments the illumination area into multiple regions, each illuminated by a separate laser beam with independent control. This allows selective illumination of only those regions containing sparse signals of interest, rather than illuminating the entire covered area uniformly. The segmentation enables the system to maintain measurement precision for sparse signals while reducing total optical energy consumption by excluding empty or non-interest areas from illumination.
Solution Approach 2:
The patent applies partial illumination by directing laser beams only at specific regions where sparse signals are expected or detected, rather than providing excessive full-area illumination. The system uses prior knowledge or preliminary detection to identify regions of interest and concentrates optical energy only there, achieving the required signal-to-noise ratio for sparse signals while avoiding waste of energy on areas without signals of interest.
2Productivity
If traditional active remote sensing systems illuminate entire covered area, then coverage rate is maintained, but quantity of substance (optical energy) increases
Solution Approach 1:
The patent divides the covered area into multiple segmented regions, each with its own illumination control. This segmentation allows the system to maintain coverage of the entire area by selectively illuminating only the necessary segments containing sparse signals, rather than illuminating the entire area uniformly. The coverage rate is maintained through coordinated selective illumination of multiple segments.
Solution Approach 2:
The patent applies local quality by providing different illumination characteristics to different regions of the covered area. Regions containing sparse signals receive targeted illumination with appropriate energy levels, while regions without signals receive no illumination or minimal illumination. This local differentiation maintains effective coverage of signal-containing areas while reducing total optical energy consumption.
3Measurement precision
If flying-spot or multipixel receiver architectures are used, then measurement capability is maintained, but device complexity increases
Solution Approach 1:
The patent extracts and removes the complex flying-spot scanning mechanism or multipixel receiver array, replacing them with a simpler single-pixel detector combined with multiple independently controllable laser beams. The measurement capability is maintained by using the simplified architecture to illuminate different regions sequentially or simultaneously with multiple beams, achieving the same sparse signal detection without the mechanical complexity of flying-spot scanners or the electronic complexity of multipixel receivers.
Solution Approach 2:
The patent replaces mechanical flying-spot scanning systems with a static single-pixel detector combined with electronically controlled multiple laser beams. The mechanical movement and complex scanning mechanisms are substituted with electronic control of light sources, significantly reducing device complexity while maintaining the ability to measure sparse signals across the covered area.
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 achieves orders-of-magnitude reduction in total energy and data requirements for wide area coverage, making it suitable for applications like wide area search with very sparse signals.
Implementation Method 1
an optical source to generate light for illuminating a target
Implementation Method 2
A pattern generator generates a pattern. The pattern is a spatial filtering pattern that enables data compression by generating sparse scattered data
Implementation Method 3
generating sparse scattered data from the target using the pattern
Implementation Method 4
detecting the sparse scattered data
Data Source
AI summary
An active optical compressive sensing system includes an optical source to generate light for illuminating a target and a pattern generator to generate a pattern. A pattern controller controls an operation of the pattern generator to cause generation of a desired pattern. The pattern is a spatial filtering pattern that enables data compression by generating sparse scattered data. Applying the pattern allows a logarithmic resource scaling.