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Optical Polarization

Polarimetry

Light, a form of electromagnetic radiation, has as one of its fundamental characteristics an intrinsic polarization. The polarization of the light refers to the direction of wave vibration in relation to the direction of propagation. The degree of polarization in reflected light is affected by a variety of factors including the illumination, surface roughness, color, and sensing geometry.

The Polarization Imaging camera measures the amount of polarized light at -45°, 0°, 45°, and 90° nearly simultaneously. These measurements are used to calculate Stokes vectors for each pixel in the image. Stokes S0 vector is the total intensity, S1 is the difference in vertical and horizontal polarization, and S2 is the difference in 45° and -45° polarization.

Degree of Linear Polarization (DOLP) is calculated according to the following relationship:

 

IED Detection

 

Research performed in 2009 tested the ability of the Bossa Nova Technology SALSA polarimetric camera to detect disturbed dirt and asphalt. Improvised Explosive Devices (IEDs) are often buried, which leaves them covered with disturbed dirt. The polarization signature of disturbed dirt was not strong compared to undisturbed dirt, but the camera was better able to distinguish between the polarization characteristics of patched or disturbed asphalt and the surrounding pavement, particularly when maximum likelihood classification was applied.

 

Disturbed asphalt with varying dirt coverage

 

Helicopter Brownout

Research performed in 2009 used Polarimetric Synthetic Aperture Radar (SAR) data from RADARSAT-2 and was analyzed for detection of helicopter brownout. Helicopter brownout occurs when downwash disturbs the dust and sand beneath the aircraft during takeoff, landing, and low altitude operations. Brownout may lead to pilot spatial disorientation and loss of control, causing helicopter damage or destruction, as well as personnel injury or death. The likelihood of helicopter brownout is related to soil moisture content, particle size distribution, and surface texture.

This research explored the polarimetric signatures of soils and determined whether these characteristics can be used to predict areas that are susceptible to helicopter brownout. Preliminary results show that helicopter brownout regions can be predicted by means of a simple threshold.  

 

   

 

(Left) RADARSAT2 Image of brownout study area at Yuma Proving Ground.  (Right)  Polarimetric radar image (VV polarization) after new Brownout Algorithm threshold values are applied. Red = Brownout likely; Sienna = Unknown/Ambiguous; Green = Non-Brownout.

 

Related Theses

Disturbance Detection in Snow Using Polarimetric Imagery of the Visible Spectrum
David C. West, Applied Physics
December 2010
Thesis Advisor: Richard C. Olsen
Second Reader: David M. Trask

The Use of Commercial Remote Sensing in Predicting Helicopter Brownout Conditions
Christine Kay Rabaja, Space Systems Operations
September 2009
Thesis Advisor: Richard C. Olsen
Second Reader: David M. Trask

Polarimetric Imaging for the Detection of Disturbed Surfaces
Michael E. Eyler, Applied Physics
June 2009
Thesis Advisor: R. C. Olsen
Second Reader: R. Harkins

The Uses of a Polarimetric Camera
Phillip Smith, Space Systems Operations
September 2008
Thesis Advisor: R. C. Olsen
Second Reader: R. Harkins

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