Noise source localization based on spatial detector arrays

2025

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.53894/ijirss.v8i4.8121
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

The purpose of this study is to investigate the applicability of a recently proposed method for wave source localization based on the Time Difference of Arrival (TDOA) and to reduce the problem to a set of linear equations. We apply TDOA to the noise source localization problem in urban environments. The study employs mathematical modeling using the three-dimensional acoustic wave equation for a point source. Simulations are performed with real noise samples recorded near a construction site. Various configurations of source positions relative to the detector array are considered. The localization accuracy is analyzed as a function of the geometric parameters of the detector array and the duration of the recorded signal segment. After determining the source coordinates, the signal amplitude in the vicinity of the source is reconstructed. Our findings indicate that the highest localization accuracy and signal reconstruction quality are achieved when the distances between the sensors are comparable to the distance to the source. The results demonstrate that, despite measurement uncertainties, the modeled approach remains robust. These insights have practical implications for the development of real-time acoustic monitoring systems in urban and industrial settings, such as noise source detection at construction sites or for public safety applications.