6/17/2023 0 Comments Nucleo l432kcOther solutions use some local infrastructure that is deployed around or inside the building. They are obtained from Inertial Measurement Units (IMU), which consist of accelerometers and gyroscopes 1. In such systems, positioning is conducted by processing data about accelerations and angular rates. Among the available solutions, Inertial Navigation Systems (INS) are often found. Due to limited capability of using Global Navigation Satellite Systems (GNSS) in such conditions, many institutions and tech companies are looking for solutions that guarantee accurate and continuous positioning inside buildings. The demand for systems that enable navigating objects in closed spaces has been constantly increasing in recent years. ![]() Based on these data, efficiency of using this kind of filtration in non-linear navigation systems has been assessed. The paper presents a personal navigation system designed by the authors, describes its unscented Kalman filter used for a mobile user position estimation and contains chosen simulation results of the tests of the filter. It also facilitates an implementation of the algorithm as non-linear transformations of a set of deterministically chosen sigma points replaces calculations of Jacobian matrices. Lack of necessity of a linearization of the dynamics and observation models leads to a higher navigation system accuracy. The linearization considers only the first term of a Taylor series and its higher terms are omitted, which degrades estimation accuracy in highly non-linear systems. ![]() The unscented Kalman filter is a suboptimal non-linear filtration algorithm, however, in contrast to algorithms such as EKF or LKF, it uses an unscented transformation (UT) as an alternative to a linearization of non-linear equations with the use of Taylor series expansion. The mentioned system is described by a linear dynamics model and a non-linear observation model, and therefore UKF can be successfully applied for its state estimation. The paper presents an Unscented Kalman Filter (UKF) for a personal navigation system using range measurements between ultrawideband radio modules for positioning. A choice of positioning algorithm is a key issue when designing a navigation system.
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