Location estimation using differential RSS with spatially correlated shadowing
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Cramér-Rao bound analysis of localization using signal strength difference as location fingerprint
INFOCOM'10 Proceedings of the 29th conference on Information communications
On ML estimation for automatic RSS-based indoor localization
ISWPC'10 Proceedings of the 5th IEEE international conference on Wireless pervasive computing
Wireless Sensor Networks: Principles and Practice
Wireless Sensor Networks: Principles and Practice
Relative location estimation in wireless sensor networks
IEEE Transactions on Signal Processing
A multidimensional scaling framework for mobile location using time-of-arrival measurements
IEEE Transactions on Signal Processing
Geometric-Polar Tracking From Bearings-Only and Doppler-Bearing Measurements
IEEE Transactions on Signal Processing
Linear Least Squares Approach for Accurate Received Signal Strength Based Source Localization
IEEE Transactions on Signal Processing
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Locating an unknown-position source using received signal strength (RSS) measurements in an accurate and low-complexity manner is addressed in this paper. Given that the source transmit power is unknown, we employ the differential RSS information to devise two computationally attractive localization methods based on the weighted least squares (WLS) approach. The main ingredients in the first algorithm development are to obtain the unbiased estimates of the squared ranges and introduce an extra variable. The second method improves the first version by implicitly exploiting the relationship between the extra variable and source location through a second WLS step. The performance of the two estimators is analyzed in the presence of zero-mean white Gaussian disturbances. Numerical examples are also included to evaluate their localization accuracy by comparing with the maximum likelihood approach and Cramer-Rao lower bound.