TY - GEN
T1 - Direction-of-Arrival Estimation of Acoustic Sources Using Acoustic Array Based on SOM and BP Neural Network
AU - Sun, Baoliang
AU - Jiang, Chunlan
AU - Song, Yuguang
AU - Xue, Kai
AU - Shi, Weike
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022/2/25
Y1 - 2022/2/25
N2 - 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.
AB - 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.
KW - Acoustic Array
KW - Angle-of-Arrival Estimation
KW - BP Neural Network
KW - Direction-of-Arrival Estimation
KW - Self-Organizing Feature Map
UR - http://www.scopus.com/inward/record.url?scp=85133801165&partnerID=8YFLogxK
U2 - 10.1145/3529570.3529605
DO - 10.1145/3529570.3529605
M3 - Conference contribution
AN - SCOPUS:85133801165
T3 - ACM International Conference Proceeding Series
SP - 205
EP - 216
BT - ICDSP 2022 - 2022 6th International Conference on Digital Signal Processing
PB - Association for Computing Machinery
T2 - 6th International Conference on Digital Signal Processing, ICDSP 2022
Y2 - 25 February 2022 through 27 February 2022
ER -