Infrasound Microphone Array Coherence Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional acoustic systems face challenges in detecting and tracking infrasound waves due to roll-off of acoustic response at lower frequencies and increased aliasing, particularly in mobile infrasound sources, requiring improved methods and hardware for accurate detection and tracking.
Innovation Solution
A method employing an equilateral triangle pattern of three infrasound microphones, acoustically shielded to filter out wind noise, with a data acquisition system analyzing coherence and time history of signals to estimate properties such as magnitude, azimuth, and elevation of infrasound events, and transmit control signals for response actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional microphones with capillary vent holes are used for infrasound detection, then the system is simple and portable, but the acoustic response rolls off at lower frequencies reducing detection accuracy
Solution Approach 1:
The system divides the detection task across multiple microphones arranged in an array, with each microphone contributing to the overall measurement. This segmentation allows the system to maintain simplicity at the individual microphone level while achieving high precision through collective processing of signals from multiple elements.
Solution Approach 2:
The patent transitions from single-point detection to spatial array detection, adding the dimensional aspect of spatial distribution. By arranging microphones in specific geometric patterns and processing signals with coherence analysis across multiple spatial dimensions, the system overcomes the frequency response limitations of individual microphones.
2Object-affected harmful factors
If widely-dispersed microphones with surface or sub-surface wind filters are used, then wind noise is filtered out, but signal coherence is reduced and aliasing is increased
Solution Approach 1:
The system employs dynamic signal processing techniques that adapt to the incoming acoustic signals. Coherence analysis and time-delay estimation are performed dynamically on the received signals, allowing the system to maintain high coherence even when microphones are dispersed and subject to wind noise, by continuously optimizing the processing parameters based on actual signal characteristics.
Solution Approach 2:
The patent introduces sophisticated signal processing algorithms as intermediaries between the physical microphones and the final detection output. These processing intermediaries include coherence calculation, time-delay estimation, and adaptive filtering techniques that recover signal coherence from the dispersed microphone inputs while maintaining wind noise rejection.
3Ease of operation
If smaller infrasound acoustic arrays are used to improve portability, then deployment is easier, but tracking accuracy of mobile emitters is reduced
Solution Approach 1:
The system performs preliminary calculations of optimal time delays and coherence thresholds based on the known array geometry and expected sound propagation characteristics. By pre-computing these parameters for the specific array configuration, the system achieves high tracking accuracy with smaller arrays, as the preliminary setup optimizes the limited spatial information available from compact deployments.
Solution Approach 2:
The patent employs adaptive parameter adjustment in the signal processing algorithms, where coherence thresholds, time-delay windows, and frequency bands are dynamically modified based on the array size and configuration. This allows smaller, more portable arrays to achieve tracking accuracy comparable to larger arrays by optimizing processing parameters to match the reduced spatial baseline.
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 approach enhances the tracking accuracy and coherence of infrasound sources over extended distances, reducing time delay resolution and improving the detection of mobile infrasound emitters across various environments, including airborne, surface, and subsurface applications.
Implementation Method 1
identifying a level of coherence of the detected infrasound signal from each possible pair of microphones
Implementation Method 2
recognizing the infrasound event via the DAS using the level of coherence and a time history of the detected infrasound signal
Implementation Method 3
The microphones in each array may be acoustically shielded to a level that is sufficient for filtering out wind noise and other undesirable ambient sound
Implementation Method 4
estimating properties of the recognized infrasound event via the DAS, including a magnitude, an azimuth angle, and an elevation angle of the infrasound event
Implementation Method 5
estimating properties of the recognized infrasound event via the DAS, including a magnitude, an azimuth angle, and an elevation angle of the infrasound event
Data Source
AI summary
A method for recognizing infrasound events includes detecting infrasonic source using one or more microphone arrays each having three equally-spaced infrasound microphones. The method includes identifying, via a data acquisition system (DAS), a level of coherence of the detected infrasonic acoustic signals from each possible pair of microphones and recognizing the infrasound source using the coherence and a time history of the detected signals. The method may include estimating source properties via the DAS, including a magnitude, azimuth angle, and elevation angle, and executing a control action in response to the estimated properties. A system includes the array and the DAS. The array may be positioned above or below ground, and may be connected to one or more aircraft in some embodiments.