The inherent and apparent optical properties (IOPs and AOPs) of seawater limit the performance of free-space optical (FSO), underwater wireless optical communication (UWOC), and imaging systems. Absorption, scattering, and downwelling irradiance are three such properties that influence system performance and often evolve independently. In situ measurements of multiple IOPs and AOPs would provide environmental sensing for fielded optical systems, but such comprehensive measurements are typically expensive or impractical. This effort analyzed existing oceanographic data sets to uncover wavelength-dependent correlations between IOPs, AOPs, test depths, and ocean depths. We then employed machine learning (ML) methods to predict the optical properties of diffuse attenuation (Kd) and backscatter (bb) using beam attenuation (c) and compared these results to ground-truth values. Predicted values of Kd and bb were well matched to their ground-truth data. Furthermore, we demonstrate ML-based Jerlov optical water type classification using beam attenuation as the optical data input. With our methods validated, we collected new optical data sets and processed them using our ML models. Results are promising and indicate future in situ classification and prediction capability. To highlight one practical application, we present a preliminary ML-enabled performance estimator for a generic FSO or UWOC system.
This effort develops and tests algorithms and a user-portable optical system designed to autonomously optimize the laser communication wavelength in open and coastal oceans. In situ optical meteorology and oceanography (METOC) data gathered and analyzed as part of the auto-selection process can be stored and forwarded. The system performs closedloop optimization of three visible-band lasers within one minute by probing the water column via passive retroreflector and polarization optics, selecting the ideal wavelength, and enabling high-speed communication. Backscattered and stray light is selectively blocked by employing polarizers and wave plates, thus increasing the signal-to-noise ratio. As an advancement in instrumentation, we present autonomy software and portable hardware, and demonstrate this new system in two environments: ocean bay seawater and outdoor test pool freshwater. The next generation design is also presented. Once fully miniaturized, the optical payload and software will be ready for deployment on manned and unmanned platforms such as buoys and vehicles. Gathering timely and accurate ocean sensing data in situ will dramatically increase the knowledge base and capabilities for environmental sensing, defense, and industrial applications. Furthermore, communicating on the optimal channel increases transfer rates, propagation range, and mission length, all while reducing power consumption in undersea platforms.
The wireless, high-data-rate transmission of information is becoming increasingly important for undersea applications that include defense, environmental monitoring, and petroleum engineering. Free-space optical (FSO) communication addresses this need by providing an undersea high-data-rate link over moderate distances (up to 100s of meters). Light transmission through seawater is maximal in the blue-green part of the optical spectrum (475 nm–575 nm), but turbidity conditions, which are dynamic, strongly influence the actual maximum. We describe the development of a laser-wavelength auto-selection algorithm and system for optimized underwater FSO communications. The use of a passive corner cube retroreflector allows all transmitter and receiver electronics to be collocated, which will be beneficial for any fielded system. First, we describe the laser test bed and retroreflector system. Next, we describe the development of the algorithm and hardware. We then describe the creation of various water types (from clear to turbid) in the laboratory using particle suspensions and dyes, which will enable wavelength-dependent transmission tests. Finally, we show experimental results from water tube tests, demonstrating wavelength auto-selection within one minute.
Wirelessly transmitting large volumes of information at high data rates underwater is becoming increasingly important for such applications as environmental monitoring and petroleum exploration and maintenance. Underwater free-space optical (FSO) communication addresses the aforementioned need by providing wireless high-data-rate links. Visible light transmission through seawater typically peaks in the blue-green spectrum (475 nm–575 nm), but local clarity conditions, which are dynamic, strongly influence the actual maximum. We describe the development of a new laser-wavelength auto-selection algorithm and system for optimized underwater FSO communication. This system has the potential to improve underwater optical link reliability for high-data-rate communications. First, we describe the laser system and water tube setup for performing optical experiments. Next, we present research on recreating various seawater types (from clear to turbid) in the laboratory using particle suspensions and dye, which will enable wavelength-dependent transmission tests. Finally, we show experimental results from optical water tube tests, and describe the development of the autoselection algorithm.
We observe critical coupling to surface phonon-polaritons in silicon carbide by attenuated total reflection of
mid-infrared radiation. Reflectance measurements demonstrate critical coupling by a double-scan of wavelength
and incidence angle. Critical coupling occurs when prism coupling loss is equal to losses in silicon carbide and
the substrate, resulting in maximal electric field enhancement.