Baoliang Sun, C. Jiang, Yuguang Song, K. Xue, Weike Shi
{"title":"基于SOM和BP神经网络的声阵列声源到达方向估计","authors":"Baoliang Sun, C. Jiang, Yuguang Song, K. Xue, Weike Shi","doi":"10.1145/3529570.3529605","DOIUrl":null,"url":null,"abstract":"Abstract-A direction-of-arrival (DOA) estimation algorithm of acoustic sources using acoustic array based on self-organizing feature map (SOM) and back propagation neural networks (BPNN) was proposed in this paper. Based on time difference of arrival (TDOA), this algorithm maps TDOA vectors with similar topology into one spatial zone, and gets the characteristic TDOA vector of this spatial zone. This characteristic TDOA vector will be input into BPNN for settlement, thus getting the DOA estimation. The blind zone of array was identified by analyzing sound localization of a rectangular pyramid array of five sensors, in which sound localization error of the acoustic array increased dramatically. However, the proposed DOA estimation algorithm can separate the blind zone and detectable zone, improving DOA estimation accuracy of acoustic sources in different regions. The simulation test and actual experiment demonstrated that the algorithm has high DOA estimation accuracy and robustness.","PeriodicalId":430367,"journal":{"name":"Proceedings of the 6th International Conference on Digital Signal Processing","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Direction-of-Arrival Estimation of Acoustic Sources Using Acoustic Array Based on SOM and BP Neural Network\",\"authors\":\"Baoliang Sun, C. Jiang, Yuguang Song, K. Xue, Weike Shi\",\"doi\":\"10.1145/3529570.3529605\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract-A direction-of-arrival (DOA) estimation algorithm of acoustic sources using acoustic array based on self-organizing feature map (SOM) and back propagation neural networks (BPNN) was proposed in this paper. Based on time difference of arrival (TDOA), this algorithm maps TDOA vectors with similar topology into one spatial zone, and gets the characteristic TDOA vector of this spatial zone. This characteristic TDOA vector will be input into BPNN for settlement, thus getting the DOA estimation. The blind zone of array was identified by analyzing sound localization of a rectangular pyramid array of five sensors, in which sound localization error of the acoustic array increased dramatically. However, the proposed DOA estimation algorithm can separate the blind zone and detectable zone, improving DOA estimation accuracy of acoustic sources in different regions. The simulation test and actual experiment demonstrated that the algorithm has high DOA estimation accuracy and robustness.\",\"PeriodicalId\":430367,\"journal\":{\"name\":\"Proceedings of the 6th International Conference on Digital Signal Processing\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-02-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 6th International Conference on Digital Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3529570.3529605\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th International Conference on Digital Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3529570.3529605","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Direction-of-Arrival Estimation of Acoustic Sources Using Acoustic Array Based on SOM and BP Neural Network
Abstract-A direction-of-arrival (DOA) estimation algorithm of acoustic sources using acoustic array based on self-organizing feature map (SOM) and back propagation neural networks (BPNN) was proposed in this paper. Based on time difference of arrival (TDOA), this algorithm maps TDOA vectors with similar topology into one spatial zone, and gets the characteristic TDOA vector of this spatial zone. This characteristic TDOA vector will be input into BPNN for settlement, thus getting the DOA estimation. The blind zone of array was identified by analyzing sound localization of a rectangular pyramid array of five sensors, in which sound localization error of the acoustic array increased dramatically. However, the proposed DOA estimation algorithm can separate the blind zone and detectable zone, improving DOA estimation accuracy of acoustic sources in different regions. The simulation test and actual experiment demonstrated that the algorithm has high DOA estimation accuracy and robustness.