Localization bias correction in n-dimensional space

In previous work we proposed a method to determine the bias in localization algorithms using 2 or 3 sensors, whose location have been already identified, for targets in 2-dimensional space by mixing Taylor series and Jacobian matrices. In this paper we extend the bias-correction method to n-dimensional space with N sensors. To illustrate this approach, we analyze the proposed method in three situations using localization algorithms. Monte Carlo simulation results demonstrate the proposed bias-correction method can correct the bias very well in most situations.