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Changes in Optical Noise Lead to Hidden Target Detection

Photonics Spectra
Jul 2017
ORLANDO, Fla. — A novel method for tracking hidden objects does so by analyzing the fluctuations in the optical noise created by the object’s movement. This approach could help advance real-time remote sensing for military and other applications, and could be useful in areas of research that involve fast-moving particles that cannot be observed directly.

Tracking hidden objects through optical noise, UCF.
The system tracks a target enclosed in a 'scattering box' that impedes direct imaging. As the object moves, it imposes fluctuations on the light coming out of the box. The light is then collected by an integrating detector, which uses an algorithm to distinguish natural noise from the fluctuations caused by the object. Courtesy of Aristide Dogariu, University of Central Florida.

Most existing technologies, including light detection and ranging (lidar), require a direct line of sight between the object and the sensor, and do not work as well when the object is obscured by clouds, fog or other conditions that scatter light.

Researchers at the University of Central Florida have demonstrated the ability to track the motion of a target that is completely surrounded and obscured by multiple scattering media. The team developed a method based on the concept of encoding the position of the target using the statistical properties of diffused radiation. Because light behaves in a predictable way, the team was able to develop statistical methods to separate natural noise from fluctuations created by the movement of the target object. The researchers also showed that the motion and relative trajectory of an enclosed target could be detected without any feedback from the inside of the obscured region.

“An object that is hidden behind some scattering diffuser is not illuminated by a spatially coherent beam,” said researcher Aristide Dogariou. “The movement of the object, the size of the object and the properties of the object affect the statistical properties of the noise-like optical field, and this effect is what we measure.”

To test their approach, the researchers enclosed a small object within a plastic box designed to scatter light. A secondary light source was created inside the box by shining a beam of coherent light onto one of the scattering walls. The target object scattered this light, and the light waves were further randomized when light passed back through the scattering walls. The light was then collected outside the box by an integrating detector, which used an algorithm to distinguish natural noise from the fluctuations caused by the object. 

“If the target that is surrounded by this enclosure starts to move, then the fluctuations that it imposes on the light coming out of the box can be detected from any direction very efficiently,” said Dogariu.

“The advantage of recovering information based on fluctuations is that it is more robust against external perturbations,” he said. “It is robust against disturbances between the light source and the object and between the object and the receiver.”

Because the system extracts information about movement in each direction independently, the approach efficiently senses position for all degrees of freedom (left-right, up-down and diagonal). In addition, because the method follows the motion of the target's center of mass, the tracking accuracy is not affected when the object tilts or rotates.

The method uses measurements of integrated scattered intensity performed anywhere outside the disturbance region, which renders flexibility for different sensing scenarios as well as low-light capabilities. 

“We are promoting a paradigm shift,” said Dogariu. “Instead of illuminating the object with a coherent beam of light, we’re illuminating it with random light. Looking at how the fluctuations of the light are modified by the interaction with the object allows us to retrieve information about the object.” 

Although the team’s novel method can detect an object hidden in an enclosure from any location outside the enclosure, it cannot identify a non-moving object. Also, it can provide only a limited level of detail about the target object. While it can detect the speed and direction of a moving object and potentially reveal the object’s size, it cannot reveal its color, material or necessarily its shape.

“You cannot recover detailed information with this method, but if you simplify the question to what you really need to know, you can solve certain task-oriented problems,” said Dogariu.

As a next step, the team is working to refine its approach to handle more complex environments, larger scenes, and scenes with lower levels of incoming light. The researchers hope that these improvements will bring the system closer to real-world applications in biomedicine, remote sensing and other areas.

Although the research involved optical experiments, the team believes that this tracking procedure could be implemented in other domains, such as acoustics and microwaves. The research was published in Optica, a publication of OSA, The Optical Society of America (doi: 10.1364/OPTICA.4.000447).


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