Polarization Change Detection for Subsurface Object Identification
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Solution Overview
Problem
Current subsurface object detection systems do not effectively utilize the degree of linear polarization (DOLP) to enhance detection capabilities, missing opportunities to supplement object detection and tracking by measuring changes in polarization states over time.
Innovation Solution
A polarization change detection system that captures images at different times to calculate changes in DOLP, generating an alert signal when significant changes indicate the presence of an object below the surface, utilizing a combination of polarized light sources, laser interferometric sensors, and acoustic modulators to agitate the surface and measure polarization changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If DOLP measurement is integrated into subsurface object detection system, then detection precision is improved, but device complexity increases
Solution Approach 1:
The PCD detector is designed to perform multiple functions: capturing images at different times, calculating DOLP changes, and generating alert signals. By integrating these functions into a single device, the system improves detection precision while minimizing the increase in device complexity.
Solution Approach 2:
The patent combines the PCD detector with existing subsurface object detection systems, merging the new DOLP measurement capability with traditional detection methods. This integration allows the system to leverage existing infrastructure while adding enhanced detection precision through polarization change analysis.
2Reliability
If image pairs are captured at different times to calculate DOLP changes, then detection reliability is improved, but loss of time increases
Solution Approach 1:
The system captures image pairs at periodic time intervals, using the temporal separation to induce and detect surface changes caused by subsurface objects. This periodic imaging approach improves detection reliability by creating measurable polarization changes while managing the time required for detection.
Solution Approach 2:
The system performs preliminary surface agitation before capturing the image pair, ensuring that subsurface objects will produce detectable surface changes during the imaging window. This preliminary action increases detection reliability by guaranteeing that the object will manifest during the measurement period.
3Measurement precision
If acoustic modulators are used to agitate the surface, then detection precision is improved, but use of energy increases
Solution Approach 1:
The system uses acoustic modulators to induce mechanical vibrations in the surface, causing subsurface objects to resonate and produce detectable surface deformations. This mechanical vibration approach improves detection precision by creating characteristic polarization change patterns while using controlled energy input.
Solution Approach 2:
The acoustic modulator operates at specific frequencies and amplitudes optimized for detecting subsurface objects, adjusting the energy parameters to achieve maximum detection precision while minimizing unnecessary energy consumption. The system tailors the agitation parameters to the detection requirements.
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 system improves the detection of subsurface objects by leveraging DOLP changes, enhancing the dynamic range of existing systems and providing a direct outline of buried objects, while maintaining a low size, weight, and power footprint, with improved Probability of Detection and reduced False Alarms.
Implementation Method 1
an acoustic modulator generating an acoustic wave to agitate objects buried beneath the surface
Implementation Method 2
a laser transmitter generating a polarized laser beam directed at the surface
Implementation Method 3
the first image and the second image capture a reflected beam from the surface
Implementation Method 4
a polarization change detection (PCD) detector that captures a first image of the surface at a first time (T1) and a second image of the surface at a subsequent second time (T2)... to determine a degree of linear polarization (DOLP)
Implementation Method 5
the processor determines a change in DOLP (ΔDOLP) from T1 to T2 in response to the surface change; and wherein the processor generates a signal in response to the ΔDOLP to alert the presence of the object below the surface
Data Source
AI summary
An object detection system uses a change in a linear polarization statistic between a first image at a first time and a second image at a second time to determine the presence or the likelihood of an object beneath a surface. The presence of the object may be determined by regions of anomalously high changes in the polarization statistic. The system may use a polarization change detection detector which may simultaneously capture images in multiple polarization channels. Further, the polarization change detection detector may be coupled with a laser interferometry system.