%0 Journal Article
%A HE Jie
%A LI Xi-fei
%A QI Yue
%A WU De-yang
%A XU Li-yuan
%T A 3-D Indoor Localization AlgorithmUsing Distance Optimization
%D 2017
%R 10.13190/j.jbupt.2017.03.004
%J Journal of Beijing University of Posts and Telecommunications
%P 37-42
%V 40
%N 3
%X Least Square is a typical three-dimensional location algorithm for time of arrival based indoor positioning system. The precondition of traditional LS algorithm is that the measurement error meets the zero mean and the equal variance. However, the multipath and non-line of sight significant in realistic indoor environment leads TOA ranging error to be non-Gaussian distribution and cannot meet the hypothesis. This conflict leads low localization accuracy. This article presents a distance optimization based least square 3-D indoor localization algorithm. The nonlinear programming method with Cayley-Menger determinant and tetrahedral geometry constraints was adopted by the proposed algorithm to optimize measured distance, which makes the ranging error fit Gaussian distribution and thus improves the localization accuracy of least square. Experiments demonstrate that the proposed distance optimization based least square 3-D localization algorithm achieves better localization accuracy and stability.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2017.03.004