The cricket compass for context-aware mobile applications
Proceedings of the 7th annual international conference on Mobile computing and networking
The anatomy of a context-aware application
Wireless Networks - Selected Papers from Mobicom'99
Localization from mere connectivity
Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Wireless Communications
A kernel-based learning approach to ad hoc sensor network localization
ACM Transactions on Sensor Networks (TOSN)
Semidefinite programming based algorithms for sensor network localization
ACM Transactions on Sensor Networks (TOSN)
IEEE Transactions on Knowledge and Data Engineering
Locality preserving CCA with applications to data visualization and pose estimation
Image and Vision Computing
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
The Journal of Machine Learning Research
Adaptive Distance Estimation and Localization in WSN using RSSI Measures
DSD '07 Proceedings of the 10th Euromicro Conference on Digital System Design Architectures, Methods and Tools
Localization of networks using various ranging bias models
Wireless Communications & Mobile Computing - ISWCS'2006
Efficient Kernel Discriminant Analysis via Spectral Regression
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Wireless Communications & Mobile Computing
Hybrid TOA-AOA estimation error test and non-line of sight identification in wireless location
Wireless Communications & Mobile Computing
Paired Measurement Localization: A Robust Approach for Wireless Localization
IEEE Transactions on Mobile Computing
A manifold regularization approach to calibration reduction for sensor-network based tracking
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Co-localization from labeled and unlabeled data using graph Laplacian
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Sensor network localization using kernel spectral regression
Wireless Communications & Mobile Computing
Indoor localization with channel impulse response based fingerprint and nonparametric regression
IEEE Transactions on Wireless Communications
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Signal-strength-based location estimation in wireless sensor networks is to locate the physical positions of unknown sensors via the received signal strengths. In this field, there are few localization researches sufficiently exploiting topology structures of the network in both signal space and physical space. The goal of this paper is to first establish two effective localization models based on specific manifold (or local) structures of both signal space and physical (location) space by using our previous locality preserving canonical correlation analysis (LPCCA) model and a newly-proposed locality correlation analysis (LCA) model, and then develop their corresponding novel location algorithms, called location estimation—LPCCA (LE—LPCCA) and location estimation—LCA (LE—LCA). Since both LPCCA and LCA relatively sufficiently take into account locality characteristics of the manifold structures in both the spaces, our localization algorithms developed from them consequently achieve better localization accuracy than other publicly available advanced algorithms. Copyright © 2011 John Wiley & Sons, Ltd.