Signal engineers work with numerous types of analytical instruments, complicated hand equations, and large structures called filters. The life of a signal processing engineer consists of collecting and processing the signal information. Gruev says, “This polarization imaging technology will enable smaller autonomous robots to roam around the first 200-300 meters where light penetrates into the water and where our technology works very well and can help during search and rescue missions.Signal engineers need years of experience, and commitment is the oldest and most rigorous communication branches. Not only is sonar unreliable over a large area, but it also often creates echoes that conceal an object’s precise location. Deep water efforts are significantly more challenging than near-surface operations, which have more technological options, and rely mainly on sonar. In order to locate the submersible at any possible depth, efforts were split into two distinct regions, near the ocean surface and near the seafloor, due to the limitations of current technology. The recent OceanGate Titan submersible search and rescue efforts have highlighted the need for accurate geolocation abilities. In situ autonomous sampling robots could provide more precise monitoring of water properties such as water temperature, salinity, oxygen levels and other related parameters. Data we do know about these bodies of water comes from monitoring via satellites 20-30 miles above the surface. Oceans account for over 70% of Earth’s surface area, yet very little is known about it. This technology presents new opportunities for people and robots to navigate underwater. Images were taken in a variety of conditions (clear vs murky waters), depths, and times of the day- even at night when underwater light intensity is significantly weaker. The team collected ~10 million images with an underwater camera and an omnidirectional lens capable of recording the polarization patterns from four sites: a freshwater lake in Champaign, IL (visibility around 0.3 m), coastal sea waters in Florida Key, FL (visibility around 0.5-3 m), sea water in the bay of Tampa, FL (visibility around 0.5 m), and a freshwater lake in Ohrid, North Macedonia (visibility exceeding 10 m). By analyzing these patterns alongside accurate date and time information, it is possible to then determine location. The patterns underwater change throughout the day, and they depend on the location of both the observer and the sun. Polarization patterns are the result of light’s transmission from the air to the water and scattering by water molecules and other particles. When those waves pass through a filter, like the water’s surface, they are forced to move in only one direction-the light has been polarized. Light waves from the sun move in all directions-it is unpolarized. “Once you have a sense of where you are, then you can start exploring and use that information to have a better understanding of the underwater world or even how animals navigate.” “We are showing for the first time, you can geolocate yourself, or a camera, in a number of different conditions, whether in open ocean waters, clear waters or low visibility waters, at day, at night, or at depth,” says Gruev. These findings were recently published in the journal eLight. This new study, led by electrical and computer engineering professor Viktor Gruev, along with computer science professor David Forsyth, enables underwater geolocalization using only optical data while providing a tool for tethered-free underwater navigation. University of Illinois Urbana-Champaign researchers have developed a novel method for underwater geolocalization using deep neural networks that have been trained on 10 million polarization-sensitive images collected from locations around the world. Viktor Gruev (left) and David Forsyth (right).

Signal processing engineer salary