TY - JOUR
T1 - Prior area searching for energy-based sound source localization
AU - Gao, Feng
AU - Cai, Yeyun
AU - Deng, Fang
AU - Yu, Chengpu
AU - Chen, Jie
N1 - Publisher Copyright:
© 2022, Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2022/12
Y1 - 2022/12
N2 - Traditional energy-based sound source localization methods have the problems of the large solution space and time-consuming calculation. Accordingly, this paper proposes to use the data collected by each acoustic sensor and their corresponding weights to adaptively initialize the prior area of a target. In this way, the potential existence range of the target is reduced and the location estimate can be determined in a small area. Specifically, we first determine the initial search point based on the current sound data and the set rules. Then, the prior location of the target is iteratively searched according to different sound energy circles’ weights. Next, the prior area of the target is determined around the prior location. Finally, the precise location of the target is further traversed to minimize the objective function, which is constructed by the weighted nonlinear least squares location (WNLS) algorithm. A series of indoor experiments are performed. The results show that our method can effectively improve the positioning accuracy by approximately 13% and greatly reduce the calculation time.
AB - Traditional energy-based sound source localization methods have the problems of the large solution space and time-consuming calculation. Accordingly, this paper proposes to use the data collected by each acoustic sensor and their corresponding weights to adaptively initialize the prior area of a target. In this way, the potential existence range of the target is reduced and the location estimate can be determined in a small area. Specifically, we first determine the initial search point based on the current sound data and the set rules. Then, the prior location of the target is iteratively searched according to different sound energy circles’ weights. Next, the prior area of the target is determined around the prior location. Finally, the precise location of the target is further traversed to minimize the objective function, which is constructed by the weighted nonlinear least squares location (WNLS) algorithm. A series of indoor experiments are performed. The results show that our method can effectively improve the positioning accuracy by approximately 13% and greatly reduce the calculation time.
KW - adaptively initialization
KW - indoor environment
KW - iterative search
KW - prior area searching
KW - sound source localization
UR - http://www.scopus.com/inward/record.url?scp=85141922413&partnerID=8YFLogxK
U2 - 10.1007/s11432-022-3568-2
DO - 10.1007/s11432-022-3568-2
M3 - Article
AN - SCOPUS:85141922413
SN - 1674-733X
VL - 65
JO - Science China Information Sciences
JF - Science China Information Sciences
IS - 12
M1 - 222204
ER -