Abstract
This paper discusses the beamforming algorithms used in developing an acoustic camera which can be used for the purpose of localizing sound sources. In order to design an acoustic camera which can display results in the form of an intensity map, it is necessary to determine the beamformed signal for all the desired incident angles, i.e. for all the desired pairs of azimuth and elevation angles. For the purpose of obtaining the beamformed signal required for localization of sound sources, two beamforming algorithms, which differ in the domain in which the beamforming is performed, were developed named respectively <i>DASt.m</i> and <i>DASf.m.</i> The aforementioned algorithms are implemented in the numerical computing environment MATLAB and furthermore compared in this paper. The beamforming was carried out using both of the aforementioned algorithms for all desired azimuth and elevation angle pairs and the obtained results were compared. In order to compare these two developed beamforming algorithms measurements were conducted in an open space using a <i>Uniform Circular Array</i> (UCA). The utilized UCA consists of 16 identical omnidirectional microphones which form a basic circular acoustic camera. The research showed that the <i>DASf.m</i> algorithm gives better results than the <i>DASt.m</i> algorithm, especially for the intensity maps of the average of the signal.
Highlights
When speaking about the concept of smart cities, designing an efficient acoustic camera could present an innovative approach to noise monitoring and in addition to detection of uncommon sound sources in sound environments familiar to the residents
The research presented in this paper showed that when designing an acoustic camera, one should follow the described procedure which contains several steps
The main idea when using the Delay and Sum (DAS) algorithm is that the signals of individual microphones can be delayed by the calculated Time Difference of Arrival (TDOA) in order to obtain a constructive summation of the signals coming from the desired direction
Summary
When speaking about the concept of smart cities, designing an efficient acoustic camera could present an innovative approach to noise monitoring and in addition to detection of uncommon sound sources (i.e. which could pose a certain risk or threat) in sound environments familiar to the residents. The formation of the directivity pattern, i.e. beamforming, is a type of signal processing which enables the localization of a sound source. One of the simplest beamforming algorithms is the Delay and Sum – DAS algorithm [8,9,10] Using such an algorithm achieves the amplification of the sound coming from a certain direction and in addition, provides the reduction of noise and reflections coming from the space surrounding the array. Sanja Grubesa et al.: The Development and Analysis of Beamforming Algorithms Used for Designing an Acoustic Camera the signal delay is added. A DJI Spark quadcopter was used as the recorded sound source [12]
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