Multiple acoustic source localization based on multiple hypotheses testing using particle approach
- Resource Type
- Conference
- Authors
- Lee, Yeongseon; Wada, Ted S.; Juang, Biing-Hwang
- Source
- 2010 IEEE International Conference on Acoustics, Speech and Signal Processing Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on. :2722-2725 Mar, 2010
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Computing and Processing
Signal Processing and Analysis
Acoustic testing
Acoustic measurements
Microphone arrays
Microwave integrated circuits
Reverberation
Position measurement
Acoustic noise
Noise measurement
Particle measurements
Time difference of arrival
time difference of arrival estimation
multiple acoustic source localization
data association
multiple hypotheses
data likelihood
- Language
- ISSN
- 1520-6149
2379-190X
Localization of multiple acoustic sources in a non-ideal environment has a number of difficulties, among which are accurate acoustic feature estimation for multiple sources and association uncertainty between measurements and their corresponding sources. This paper focuses more on the latter and proposes an algorithm based on a multiple-hypothesis framework for both a measurement model and a measurement association model to localize multiple sources. A conditional data likelihood model based on a measurement hypothesis is proposed and implemented using particles. Simulation results demonstrate that the proposed algorithm is capable of localizing the positions of multiple sources with a small number of microphones without any prior knowledge when the amount of reverberation is moderate.