Improved Height Estimation Using Extended Kalman Filter on UWB‐Barometer 3D Indoor Positioning System

Abstract

Indoor 3D positioning system requires precise information from all three dimensions in space, but measurements in the vertical direction are usually interfered by sensors properties, unexpected obstructions, and other factors. Thus, accuracy and robustness are not guaranteed. Aiming at this problem, we propose a novel sensor fusion algorithm to improve the height estimation for a UWB-barometer integrated positioning system by introducing a pseudo reference update mechanism and the extended Kalman filter (EKF). The proposed fusion approach effectively helps with sensing noise reduction and outlier restraint. The results from numerical experiment investigations demonstrate that the accuracy and robustness of the proposed method achieved better improvement in height determination.

Three-Dimensional Indoor Positioning Scheme for Drone with Fingerprint-Based Deep-Learning Classifier

“…Year Published Hardware Methods [9] Barometer sensor Barometer sensor combined with received signal strength (RSSI) fingerprinting to develop an indoor positioning algorithm based on a 3D smartphone [10] Bluetooth Bluetooth-based 3D indoor positioning scheme based on RSSI fingerprinting and bidirectional ranging [11] UWB barometer UWB barometer 3D indoor positioning system, including a pseudo-reference update mechanism and the extended Kalman filter [12] Built-in sensors Precise 3D indoor localisation and trajectory optimisation framework combining sparse Wi-Fi fine-time measurement anchors and built-in sensors [13] Mobile phone sensors Method for indoor positioning in three smartphone carrying modes (i.e., texting, calling, and swinging), based on data derived from an accelerometer, magnetometer, gyroscope, and gravity and pressure sensors [14] Visible LED Real-life 3D indoor navigation localisation system using visible LED lights placed on the ceiling [15] Pedestrian dead-reckoning Adaptive pedestrian dead-reckoning method to improve the robustness and accuracy of three-dimensional positioning by adjusting parameters based on different phone carrying modes, pedestrian activities, and individual characteristics [16] Visible light Novel 3D indoor visible-light positioning algorithm based on spatial modulation…”

“…The stability of Bluetooth devices can help overcome the limitations of the traditional RSSI fingerprinting scheme, and the two-way ranging scheme can reduce the errors in single ranging, thereby improving the positioning accuracy. Furthermore, to address the limitations in vertical direction measurement in 3D indoor positioning systems, attributable to sensor properties and unexpected occlusion, a novel sensor fusion algorithm [11] has been proposed. This algorithm improves the height estimation accuracy of a UWB barometer integrated positioning system by introducing a pseudo-reference update mechanism and an extended Kalman filter.…”

Influence of Measured Radio Map Interpolation on Indoor Positioning Algorithms

“…By combining an accelerometer, gyroscope and magnetometer the direction, orientation and speed of movement of the user can be obtained [27], [28]. Additionally with a barometer the movement in vertical axis can be roughly determined [25], [29].…”

A Hybrid Indoor Altimetry Based on Barometer and UWB

“…However, most commercial environments currently do not have extra reference base stations, and communication between devices may also limit the widespread adoption of this method. To avoid setting up a new reference base station, Li et al [15] fused the estimated altitude based on the barometer and the estimated altitude based on UWB using the extended Kalman filter to achieve high-precision altitude measurement. However, the estimated altitude based on UWB is obtained through the triangle center-ofmass algorithm, which sometimes fails to converge when the indoor UWB base stations are coplanar, resulting in inaccurate altitude estimation.…”