Sound source localization (SSL) is a broad field, with many important application areas. In outdoor environments SSL systems can, among other things, be used to increase citizens’ safety by detecting and locating abnormal sounds such as gunshots or screams. Localization is a complex field, in the case of an outdoor setting, the sound signal is affected by weather conditions, noise, and objects blocking the propagation path. Furthermore, challenges concerning implementing cost-effective algorithms, robustness, accuracy, and balancing trade-offs, still remain. SSL is a field of intense research, and new studies are continuously published. However, to the best of the authors knowledge, there are no recent reviews of state of the art SSL solutions, applicable in an outdoor urban setting. Hence, this study provides a knowledge base concerning current SSL approaches, intended for the aforesaid environment, and to this end a systematic literature review was performed. The review consisted of a total of 43 studies, published between 2017-2021. From the extracted data, a taxonomy of currently seen design principles was developed. Additionally, both the applied measurement techniques and the positioning methods were defined. It can be seen from the result that classical methods such as direction of arrival and time difference of arrival still are the most used principles in research. However, learning-based approaches have seemingly started to attract more attention. Furthermore, a general description of the SSL approaches has been presented. Thus, the knowledge base provided by this study contains both information on what current state of the art techniques are most commonly adopted as well as the basic ideas behind these principles.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-109297 |
| Date | January 2022 |
| Creators | Malmgren, Anna |
| Publisher | Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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