Modeling Acoustic Telemetry Detection Ranges in a Shallow Coastal Environment

Abstract

Acoustic telemetry is a popular way of monitoring underwater environments and habitats, but an understanding of the detection range and efficiency of the receivers in variable conditions can provide a significant advantage over the detections alone. Receivers can be attached or integrated into autonomous underwater vehicles (AUVs) allowing wide spatial coverage for telemetry networks while collecting environmental data. The integration of calculated sound speeds and received pings gives an estimation of variation in detection efficiency due to changes in environmental conditions, allowing underwater network users to better quantify the range of reliable detection. Data from a Slocum glider deployed over an array of 16 moored telemetry instruments on the inner shelf off Georgia in 2019 and 2020 indicate that detection efficiency and range vary seasonally. Beam density analysis using ray tracing is proposed as a novel approach that quantifies probability of detection as a function of range, modeling sound speed variability and propagation using co-located temperature and salinity measurements. This approach is validated through comparison of modeled to observed distributions, which suggests that beam density analysis is a promising method to remotely estimate detection efficiency in real time. This real time capability can be leveraged through adaptive sampling in the design and implementation of robotic acoustic telemetry networks.