Statistical characteristics of landmark-based localization performance

Landmark-based localization is a prevalent method to obtain the position information of objects, such as autonomous robots, in industries. This study investigated the performance characteristics of landmark-based localization based on the popular multilateration algorithm from new perspectives. Two performance metrics were used, namely, accuracy and precision, which are defined as the mean and standard deviation of root mean squared error over the entire localization region. The general formulations for the two metrics were obtained, and the computation was accomplished by Monte Carlo simulation. The simulation was performed under a simplified localization configuration, and the following system factors were systematically studied, namely, landmark layout, landmark number, target location distribution, and ranging error type. The quality of landmark layout was, for the first time, quantitatively assessed. Optimal layout can be obtained by minimization of the localization accuracy and precision values with regard to the quality index. It was found that the index represented by the area of polygon enclosed by the landmarks is an excellent measure of layout quality. Also, the improvement of localization performance can be achieved by distributing landmarks more evenly, using more landmarks, placing the target closer to the center of localization region, or reducing the ranging errors. Furthermore, it was also demonstrated that the findings in simulation are generally confirmed by the experimental results using active radio-frequency identification (RFID) devices.