Uncertainty evaluation of 3D coordinates and tuning of parameters for Kalman and particle filters - Keow, Chin Shan (Nanyang Technological University, 2022)
In the era of digital transformation, indoor localization has been widely applied to the industry such as manufacturing, supply chain and healthcare services. While positioning accuracy is a key metric to determine the quality of adopted indoor localization, 3D measurement contributes impactfully as the influencing factor of the accuracy. Uncertainty 3D measurement can be analyzed through some defined mathematical models. Nonetheless, this uncertainty can also be analyzed by implementing algorithm for estimation purposes. The main purpose of this project is to adopt some filter algorithms to evaluate the 3D measurement through the estimation of unknown variables according to the measurements recorded over the time. Kalman filter has been found to be useful in the past researches and works that has been recognized. In this report, tunable parameters of the filter will be discussed. The relationship between each parameter and different propagation will need to be observed and enhancement will be carried out. Finally, there will be a final model to be proposed according to the result metrics such as computational efficiency and accuracy.