Software-Defined Hydrophone for Multi-Band Underwater Signal Analysis
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Solution Overview
Problem
Existing passive acoustic monitoring (PAM) systems face challenges in accurately analyzing underwater audio signals due to overlapping sounds across large bodies of water, requiring multiple frequency-specific devices and significant computing resources, which limits scalability and deployment in remote locations with limited power access.
Innovation Solution
A software-defined hydrophone with acoustic sensor functions and machine learning capabilities, allowing dynamic configuration of digital signal processing (DSP) functions and frequency bands via software, enabling parallel analysis of multiple audio channels and reducing power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple frequency-specific devices are used to analyze overlapping underwater audio signals, then measurement precision is improved, but device complexity and quantity increase
Solution Approach 1:
The patent implements a single acoustic sensor capable of performing multiple frequency band analyses simultaneously through software-defined functions. The acoustic sensor can be dynamically reconfigured to analyze different frequency bands (e.g., low frequency for whale songs, high frequency for crab sounds) without requiring separate hardware devices for each frequency range, thus achieving multi-functionality that resolves the contradiction between measurement precision and device complexity
Solution Approach 2:
The system employs dynamic reconfiguration of DSP functions and frequency bands through software control. The acoustic sensor can adaptively switch between different frequency bands and processing modes based on the specific monitoring requirements, allowing one device to perform the work of multiple static devices while maintaining high measurement precision across different acoustic scenarios
2Productivity
If multiple acoustic channels are analyzed in parallel, then productivity is improved, but use of energy increases
Solution Approach 1:
The system dynamically activates only the necessary acoustic channels and DSP functions based on current monitoring priorities and environmental conditions. Instead of continuously processing all channels at full capacity, the controller can scale down processing intensity or deactivate less critical channels during periods of low activity, thereby maintaining high productivity when needed while reducing energy consumption during normal operation
Solution Approach 2:
The patent changes processing parameters such as sampling rate, frequency band width, and channel activation status based on operational requirements. By adjusting these parameters dynamically, the system can achieve high throughput for critical signals while operating in a lower-power mode for less critical monitoring tasks, effectively decoupling productivity from continuous high energy consumption
3Measurement precision
If significant computing resources are allocated to signal processing, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The system applies partial processing to acoustic signals based on their importance and characteristics. Instead of applying full computational resources to all signals uniformly, the controller can apply intensive processing only to signals of interest (e.g., suspected whale songs or vessel noises) while using lighter processing for background ambient sounds, thereby achieving high measurement precision for critical detections without the energy cost of processing every signal at maximum intensity
Solution Approach 2:
The patent dynamically adjusts processing parameters such as FFT size, filter complexity, and detection thresholds based on signal characteristics and operational context. This allows the system to maintain high measurement precision when analyzing critical signals while reducing computational load and energy consumption during routine monitoring, effectively balancing accuracy requirements with power availability
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
Enables scalable, accurate, and power-efficient underwater acoustic monitoring by dynamically reconfiguring DSP functions and channels, simplifying deployment and enhancing marine observation accuracy.
Implementation Method 1
A first underwater audio signal is received by the first hydrophone
Data Source
AI summary
Disclosed techniques enable improved analysis of acoustic data. An acoustic sensor that includes one or more acoustic channels is accessed. The acoustic sensor is coupled to one or more hydrophones. A first hydrophone is associated with a first acoustic channel within acoustic channels. The acoustic sensor and the hydrophones are deployed in a body of water. One or more digital signal processing (DSP) functions of the acoustic sensor are programmed via software. A first DSP function is associated with a first frequency band and the first acoustic channel. A first underwater audio signal is received by the first hydrophone. The first underwater audio signal is analyzed by the acoustic sensor which includes sampling the first underwater audio signal. The analyzing is based on the first DSP function associated with the first acoustic channel.