Indoor location estimation based on the RSS method using radial log-normal distribution

• Published in: 2015 16th IEEE International Symposium on Computational Intelligence and Informatics (CINTI) pp. 29 - 34
• Main Authors: Okusa, Kosuke, Kamakura, Toshinari
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.11.2015
• Subjects: Computational intelligence; Estimation; Least mean square methods; Log-normal distribution; Radio transmitters; Receivers
• DOI: 10.1109/CINTI.2015.7382938

We study the problem of analyzing indoor location estimation by statistical radial distribution model. In this study, we suppose the observed distance data between transmitter and receiver as a radial log-normal distribution. We estimate the subject's location using marginal likelihoods of radial lognormal distribution. To demonstrate the effectiveness of our method, we conducted two sets of experiments, assessing the accuracy of location estimation of static case and dynamic case. In static experiment, subject is stationary state in some places in the chamber. This experiment is able to measure the precise performance of proposed method. In dynamic experiment, subject is move around in the chamber. This experiment is able to measure the suitability for practical use of proposed method. As a result, our method shows high accuracy for the static case indoor spatial location estimation.