Performance limits in sensor localization
Automatica (Journal of IFAC)
Emitter localization using received-strength-signal data
Signal Processing
Accurate and simple source localization using differential received signal strength
Digital Signal Processing
Weighted Linear Least Square Localization Algorithms for Received Signal Strength
Wireless Personal Communications: An International Journal
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A conventional approach for passive source localization is to utilize signal strength measurements of the emitted source received at an array of spatially separated sensors. The received signal strength (RSS) information can be converted to distance estimates for constructing a set of circular equations, from which the target position is determined. Nevertheless, a major challenge in this approach lies in the shadow fading effect which corresponds to multiplicative measurement errors. By utilizing the mean and variance of the squared distance estimates, we devise two linear least squares (LLS) estimators for RSS-based positioning in this paper. The first one is a best linear unbiased estimator while the second is its improved version by exploiting the known relation between the parameter estimates. The variances of the position estimates are derived and confirmed by computer simulations. In particular, it is proved that the performance of the improved LLS estimator achieves Cramér-Rao lower bound at sufficiently small noise conditions.