A grouping protocol for improving localization bias-correction

In the previous work we proposed a method to correct the bias in localization algorithms in n dimensional space with an arbitrary number of sensors at known locations. The key mathematical tools used in the bias-correction method are Taylor series and Jacobian matrices. In this paper an enhancement protocol based on a grouping idea is proposed. The proposed protocol can be used when extra sensors are introduced in order to improve the localization accuracy while avoid significantly increasing the computational cost. Monte Carlo simulation results demonstrate the performance of the proposed grouping protocol.