Indoor Positioning and Tracking by Coupling IMU and UWB with the Extended Kalman Filter

Abstract

The goal of making each related object “location aware,” or “answering the where,” could boost the value of Internet of Things applications (IoT). Ultra-wideband (UWB) is applied in many services. UWB is used as the Real-Time Location System (RTLS), empowering the influence of things to come. Its reception in consumer smartphones and industrial indoor frameworks has made the RF technology watch regardless of the industry. It evident that understanding UWB is indispensable to planning future-evidence target tracking and indoor positioning systems with high accuracy that carries indoor insight into the most confounded assembled conditions. The target’s location is estimated by using the Iterative method, which uses time of arrival (TOA) values. The Mean Square Error is calculated and compared between 2D and 3D environments. This paper also reports the design of an object tracker that uses Inertial Measurement Unit (IMU) and Extended Kalman Filter (EKF). The performance of the EKF is displayed using simulated target tracking in a 3D environment.