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To improve localization accuracy: A two-objective optimization method

It is well known that the sensor-anchor geometry and Non-Line-Of-Sight (NLOS) can significantly degrade the wireless localization accuracy. In order to settle the above problems and improve the localization accuracy, a two-objective optimization method is proposed in this paper, which can provide a selective-weighted vector for the following Maximum Likelihood Estimation (MLE). The proposed two-objective method includes two objects: one is the optimal sensor-anchor geometry, the other is the optimal residuals combination. The residuals are obtained from the differences between the location estimations by the correlation coefficient method and the ML based method respectively. Experiment utilizing received signal strength (RSS) measurements validate that the proposed method is effective in environments with mixed LOS/NLOS dynamic obstacles.