Dynamic fine-grained localization in Ad-Hoc networks of sensors
Proceedings of the 7th annual international conference on Mobile computing and networking
A Statistical Modeling Approach to Location Estimation
IEEE Transactions on Mobile Computing
Distributed localization in wireless sensor networks: a quantitative comparison
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Wireless sensor networks
Wireless sensor network localization techniques
Computer Networks: The International Journal of Computer and Telecommunications Networking
A Survey on Wireless Position Estimation
Wireless Personal Communications: An International Journal
Experimental comparison of RSSI-based localization algorithms for indoor wireless sensor networks
Proceedings of the workshop on Real-world wireless sensor networks
Bias-correction in localization algorithms
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Relative location estimation in wireless sensor networks
IEEE Transactions on Signal Processing
Survey of Wireless Indoor Positioning Techniques and Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Challenge: towards distributed RFID sensing with software-defined radio
Proceedings of the sixteenth annual international conference on Mobile computing and networking
Accurate and simple source localization using differential received signal strength
Digital Signal Processing
International Journal of Sensor Networks
Rethinking Stream Ciphers: Can Extracting be Better than Expanding?
Wireless Personal Communications: An International Journal
Weighted Linear Least Square Localization Algorithms for Received Signal Strength
Wireless Personal Communications: An International Journal
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We consider the problem of RSS-based indoor localization with Maximum Likelihood (ML) estimation techniques in low-cost Wireless Sensor Networks (WSN). In the perspective of fully automated methods, we consider the problem of channel and position estimation as coupled problems. We compare via simulations the approaches of separate and joint ML estimation, plus a third method based on multi-lateration. We find that channel estimation via simple linear regression combined with ML localization has the potential to achieve good accuracy while keeping a very low level of computational and implementation complexity. We also find that in 3D localization the vertical error on the z-axis is considerably larger than the horizontal error on the xy-plane. This is due to the limited vertical offset that can be imposed to anchor beacons in "flat" buildings where the height is considerably smaller than the horizontal dimensions.