Acoustic Vector Sensor Array for Underwater Source Localization
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Solution Overview
Problem
Existing acoustic source localization systems face challenges in deploying large hydrophone arrays in energetic environments, such as near marine renewable energy devices, due to their size and footprint, and are hindered by the affordability and limitations of acoustic vector sensors, including motion-induced noise and electronic self-noise.
Innovation Solution
A compact array of acoustic vector sensors integrated into an underwater platform that measures both acoustic pressure and particle velocity, with data streamed in real-time to a surface buoy for intermediate processing and transmission to a cloud server for user exploitation, enabling accurate localization of underwater noise sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If large hydrophone arrays are used for acoustic source localization, then localization accuracy is improved, but deployment difficulty increases in energetic environments
Solution Approach 1:
The system segments the acoustic sensing function by using multiple compact vector sensor units distributed in space rather than one large hydrophone array. Each vector sensor measures 3D particle velocity and pressure independently, and their measurements are combined through triangulation to achieve localization, thus distributing the functionality across smaller, more deployable components.
Solution Approach 2:
The invention transitions from scalar pressure measurement (hydrophones) to vector particle velocity measurement (acoustic vector sensors), adding directional information as a new dimension. This enables bearing estimation and source localization with fewer sensors, reducing the spatial footprint required for deployment.
2Loss of information
If acoustic vector sensors are used instead of hydrophones, then directional information is obtained, but sensor cost and noise susceptibility increase
Solution Approach 1:
The system merges measurements from multiple acoustic vector sensors to achieve robust source localization. By combining data from several sensors with independent noise characteristics, the system benefits from spatial diversity to suppress noise while maintaining directional information capability.
Solution Approach 2:
The system employs adaptive signal processing with feedback mechanisms to suppress motion-induced noise and electronic self-noise. The processing algorithm continuously adjusts based on measured signals to distinguish between sensor noise and actual acoustic sources, improving signal quality in real-time.
3Productivity
If real-time data streaming is implemented, then immediate processing capability is improved, but data transmission requirements increase
Solution Approach 1:
The system extracts only the essential acoustic parameters (particle velocity components and pressure) needed for source localization and streams them in real-time, rather than transmitting complete raw sensor datasets. This selective extraction reduces data volume while maintaining the capability for immediate processing and localization.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution provides accurate and efficient characterization of underwater noise sources, including marine mammals and fish, by triangulating particle velocity vectors, overcoming the limitations of traditional hydrophone arrays and enhancing understanding of acoustic propagation effects on marine life.
Implementation Method 1
A vector sensor measures three-dimensional (3D) acoustic particle velocity in addition to acoustic pressure on a single sensor, which inherently provides directional information (acoustic bearing) to a source of sound.
Implementation Method 2
A vector sensor array (VSA) can, therefore, triangulate individual measured bearings to provide sound source localization
Data Source
AI summary
An acoustic monitoring system characterizes, classifies, and geo-locates anthropogenic and natural sounds in near real time. The system includes a compact array of three acoustic vector sensors, which measures acoustic pressure and the three-dimensional particle velocity vector associated with the propagation of an acoustic wave, thereby inherently providing bearing information to an underwater source of sound. Beamforming techniques provide sound source localization, allowing for characterization of the acoustic signature of specific underwater acoustic sources.