Abstract
This letter introduces an RSS-based framework (termed Source Position Estimation for Anchor position uncertainty Reduction - SPEAR) for joint estimation of the positions of a wireless transmitter source and the corresponding measuring anchors. The framework exploits the imprecise anchor position information using non-Bayesian estimation and employs a novel Joint Maximum Likelihood (JML) algorithm for reliable anchor and agent position estimations. It proposes to use the iterative Trust Region (TR) strategy as a solution to the JML nonlinear minimization problem. Simulation results show that the JML results in source localization improvements (compared to the ML that ignores the anchor position uncertainty) and provides a more reliable anchors? positions estimates.
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