Acoustic camera
[6] It designates nowadays any transducer array used to localize sound sources (the medium is usually the air), especially when coupled with an optical camera.
This method has many advantages – it is robust, easy to understand, highly parallelizable (because each direction can be computed independently), versatile (there exist many types of beamformers), and it is relatively fast.
Various methods have been introduced to reduce the artifacts such as DAMAS[7] or to take in account correlated sources such as CLEAN-SC,[8] both at the price of a higher computational cost.
Two-dimensional mapping approximates three-dimensional surfaces into a plane, allowing the distance between each microphone and the focus point to be calculated relatively easily.
The camera is frequently applied to improve the noise emission of vehicles (such as cars, airplanes[10]), trains, structures—such as wind turbines[11] and heavy machinery operations such as mining [12] or drilling.
Acoustic cameras are not only used to measure the exterior emission of products but also to improve the comfort inside cabins of cars,[9] train or airplanes.
Spherical acoustic cameras are preferred in this type of application because the three-dimensional placement of the microphone allows to localize sound sources in all directions.
Epidemiologist Erica Walker has said this is a "lazy" solution to the problem of noise, and expressed concern acoustic cameras could be used to over-police ethnic minority neighbourhoods.
An inherent challenge related to the dynamic range of acoustic cameras lies in its dependency on the sound's wavelength and the size of the array.
These physical constraints pose difficulties for far-field acoustic cameras aiming to resolve multiple low-frequency sources.
This underlines the unique challenges faced in enhancing the dynamic range of acoustic cameras, particularly in applications involving low-frequency sounds.
The lowest frequency that can be localized with a far-field acoustic camera is primarily determined by the size of the array's aperture (its largest dimension).
Challenges arise when dealing with low-frequency issues, particularly those below 300 Hz, as they require large array sizes for effective sound source localization.
Because of this, signal processing is frequently done after the recording of data, which can hinder or prevent the use of the camera in analyzing sounds that only occur occasionally or at varying locations.
Signal processing optimizations often focus on reduction of computational complexity, storage requirements, and memory bandwidth (rate of data consumption).
