Autonomous, Long-Duration, Directional Ambient Sound Sensor

OUSD (R&E) CRITICAL TECHNOLOGY AREA(S): Trusted AI and Autonomy OBJECTIVE: Develop an autonomous, long-duration, directional ambient sound sensing system capable of being integrated into a variety of platforms including floats, gliders, and ocean observation buoys. The system should output soundscape-related information in a manner that is scaled to match platform communications bandwidth. DESCRIPTION: Sound waves generated by natural (both abiotic and biotic) and anthropogenic sources convey information about both the source and the environment in which they travel. Underwater recordings of ambient sound have been previously used to estimate local weather (wind, rain), to identify the presence/absence of marine organisms, and, particularly when directional information is included, to characterize the undersea environment. These systems, however, have not found widespread usage in the near-real-time reporting systems that currently exist in ocean observing networks (e.g., systems of floats and gliders, observational buoy networks). This STTR topic seeks to develop a low power (~1 W), long duration (months to years) system that can be widely integrated into ocean observing networks. Successful solutions will include onboard processing to provide generalized soundscape information, including sound intensity levels as a function of frequency and direction (both horizontal and vertical), event detection, and scalable reporting options that can be matched to host platforms (e.g., low data rate satellite communications, moderate data rate cellular communications). The system should output soundscape-related information in a manner that is scaled to match platform communications bandwidth. Innovations are anticipated at both the sensing level, particularly for the directionality of ocean sound and its use in characterizing the ocean environment, and at the onboard processing level where the information content of ambient sound is efficiently and autonomously extracted from the raw data. The successful solution will be scalable to wide-region distributed sensing (e.g., 10's to 100's of sensors throughout a sea, or 1000's of sensors distributed throughout the world's oceans). PHASE I: Develop an initial concept design that can accommodate various host platforms including floats, gliders, and observation buoys. The concept design should include sensing concept and configuration, mechanical packing, power consumption, communication interfaces, sensor (re)calibration methodology, algorithms to extract the information content of the ocean sound, and estimated data rate(s). Algorithms are expected to be tested on previously collected or simulated data (e.g., passive acoustic data held by the NOAA National Centers for Environmental Information). PHASE II: Develop a prototype autonomous, long-duration, directional ambient sound sensor, integrate it into a host platform, and use real-world data to analyze its performance including sensitivity, self-noise, dynamic range, direction-resolving capability, power consumption, longevity, and sensitivity stability. PHASE III DUAL USE APPLICATIONS: Demonstrate the use of a regional network of sensors (e.g., 10's of systems) including deployment, data collection/communication, and data analysis (e.g., generalized soundscape information and event detection). Naval applications of this system include the capability to validate and fine-tune ambient sound models and databases in operational environments, including real-time updates in the temporally and spatially varying ocean. Although the direct sensor output data will be unclassified, its use in direct coordination with Navy ambient sound models and databases may be CUI or classified. Commercial application of this technology is anticipated to be tied to the blue economy, including the detection of protected species in areas of interest to commercial fishing and offshore wind technologies. REFERENCES: 1. Vagle, S., Large, W. G., & Farmer, D. M. (1990). An evaluation of the WOTAN technique of inferring oceanic winds from underwater ambient sound. Journal of atmospheric and oceanic technology, 7(4), 576-595. https://doi.org/10.1175/1520-0426(1990)0072.0.CO;2 2. Van Uffelen, L. J., Roth, E. H., Howe, B. M., Oleson, E. M., & Barkley, Y. (2017). A Seaglider-integrated digital monitor for bioacoustic sensing. IEEE Journal of Oceanic Engineering, 42(4), 800-807. https://doi.org/10.1109/JOE.2016.2637199 3. Siderius, M., & Gebbie, J. (2019). Environmental information content of ocean ambient noise. The Journal of the Acoustical Society of America, 146(3), 1824-1833. https://doi.org/10.1121/1.5126520 KEYWORDS: Ambient Noise; Soundscape; Sonar; Autonomous; Ocean Observing; Environmental Sensing