Convex Optimization
Monte Carlo Statistical Methods (Springer Texts in Statistics)
Monte Carlo Statistical Methods (Springer Texts in Statistics)
Challenges for efficient communication in underwater acoustic sensor networks
ACM SIGBED Review - Special issue on embedded sensor networks and wireless computing
Localization in underwater sensor networks: survey and challenges
WUWNet '06 Proceedings of the 1st ACM international workshop on Underwater networks
AUV-Aided Localization for Underwater Sensor Networks
WASA '07 Proceedings of the International Conference on Wireless Algorithms,Systems and Applications
Acoustic propagation considerations for underwater acoustic communications network development
ACM SIGMOBILE Mobile Computing and Communications Review
Localization of networks using various ranging bias models
Wireless Communications & Mobile Computing - ISWCS'2006
Motion-aware self-localization for underwater networks
Proceedings of the third ACM international workshop on Underwater Networks
Prospects and problems of wireless communication for underwater sensor networks
Wireless Communications & Mobile Computing - Underwater Sensor Networks: Architectures and Protocols
Cooperative localization for autonomous underwater vehicles
Cooperative localization for autonomous underwater vehicles
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Stratification Effect Compensation for Improved Underwater Acoustic Ranging
IEEE Transactions on Signal Processing - Part I
Network Localization with Biased Range Measurements
IEEE Transactions on Wireless Communications
Underwater localization and tracking of physical systems
Journal of Electrical and Computer Engineering - Special issue on Underwater Communications and Networking
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We consider cooperative positioning using acoustic range measurements for underwater sensor networks, including networks formed by autonomous unmanned underwater vehicles (UUVs). Severe multipath scattering from the seabed and ocean surface can result in inaccurate range measurements. In an inhomogeneous medium, such as sea water, the direct path is not necessarily the strongest path or the first arrival. Then, the range measurements based on the first or strongest arrival could be significantly biased. We introduce herein a new centralized cooperative positioning algorithm, referred to as the weighted Gerchberg-Saxton algorithm (WGSA), for underwater sensor networks. We assume that for each acoustic ranging channel, multiple range measurements corresponding to several propagation paths, one of which is the direct path, are available for cooperative positioning. Since it is unknown a priori which path is the direct path, we must identify it first. We show that WGSA can be used to automatically identify the direct path. We also show using numerical examples that WGSA is an effective and efficient approach to cooperative positioning in underwater sensor networks.