Low complexity source localization algorithms in sensor networks
PE-WASUN '05 Proceedings of the 2nd ACM international workshop on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks
Channel aware target localization with quantized data in wireless sensor networks
IEEE Transactions on Signal Processing
Energy based acoustic source localization
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Considerations on acoustic source localization
CIMMACS'07 Proceedings of the 6th WSEAS international conference on Computational intelligence, man-machine systems and cybernetics
A new energy efficient target detection scheme for pervasive computing
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part IV
A speaker localization system for lecture room environment
MLMI'06 Proceedings of the Third international conference on Machine Learning for Multimodal Interaction
Automation and Remote Control
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We develop four maximum likelihood (ML) methods to localize a moving target using a network of acoustical sensor arrays. Each array transmits a direction-of-arrival (DOA) estimate to a central processor, which employs one of the localization techniques. The four ML approaches use different target signal models where the time retardation factor for the target position and the degradation of the target signal through the air may or may not be included in the model. We compare these methods along with a linear least squares approach through a number of simulations at various signal to noise levels.