Acoustic system reliably tracks offshore threats with sparse sensors
On Distributed Sensing and Adversarial Localization of Narrowband Acoustic Sources for Offshore Data Center Monitoring
Robotics
Summary
Protecting offshore data centers from harmful sounds is tricky because sensors can only hear certain frequencies, and those sounds can seem confusing or misleading. The authors created a method that uses a moving sensor along with several fixed ones to better pinpoint where these sounds come from. They tested their approach in computer simulations, robot demonstrations, and real ocean conditions, achieving good accuracy in locating and following the sound sources. This work shows it’s possible to monitor large ocean structures using sound even when the signals are hard to interpret.
What this means in practice
- •For offshore infrastructure operators: Enhance monitoring systems to locate hostile acoustic sources threatening offshore data centers using sparse sensor deployments combined with mobile receivers.
- •For marine robotics teams: Implement acoustic tracking for underwater robots to detect and follow narrowband sound sources in noisy and uncertain environments.
Authors
Adnan Abdullah, David Blow, Harsha Gundala Sureshbabu, Dongyoon Joung, Sara Rampazzi, Md Jahidul Islam
Abstract
This report investigates an acoustic surveillance framework for localizing and tracking narrowband adversarial acoustic sources that threaten offshore data centers. Unlike conventional sound source localization (SSL) methods that rely on broadband signals and compact receiver arrays, the considered scenario involves narrowband emissions and sparse sensors. In such scenarios, the observed time-difference-of-arrival (TDOA) measurements are aliased and produce an ambiguous solution space, rendering conventional localization methods ineffective. To address this challenge, we integrate a mobile receiver that temporarily forms anchor pairs with selected fixed receivers, constraining the feasible solution space. The proposed two-stage pipeline first estimates the initial source position using anchor constraints, then initializes a particle filter that jointly tracks source position and velocity using one live anchor measurement and quality-adaptive fixed-pair measurements. We evaluate the proposed method through Monte Carlo acoustic simulations, ROS-Gazebo robotic demonstrations, and open-water field experiments. Our framework achieves a localization success rate of 91% in simulation, while 9 of 10 field trials show tracking error below 2m under receiver-position uncertainty and noisy sensing conditions. These findings demonstrate the feasibility of passive acoustic surveillance for protecting large-scale infrastructure against acoustic threats.