A Novel Geometry-Based Model for Localization Based on Received Signal Strength

A novel geometry-based model (GBM) is proposed to locate the transmitter based on received signal strength (RSS), where there is no anchor point. Previous studies were mostly based on maximum likelihood (ML) estimator. The novel GBM estimator gives a new approach for localization based on the geometrical significance, which is to find a point with least sum of distance to the edge of circles. The corresponding Cramer-Rao Lower Bound (CRLB) of unbiased estimator and a time-saving Monte Carlo approach to the CRLB of GBM are derived. In addition, the confidence interval of Root-Mean-Square Error (RMSE) is also derived based on Central Limit Theorem in order to make sure the results of simulation are statistical significant. The simulation results demonstrate that GBM estimator can achieve much higher accuracy compared to ML. The proposed GBM algorithm is verified with experimental data set from commercial cellular networks, and shows better performances.