Loosely Coupled GNSS and UWB with INS Integration for Indoor/Outdoor Pedestrian Navigation

Area of Science:

• Navigation Systems
• Sensor Fusion
• Geomatics Engineering

Background:

• The proliferation of location-based services (LBS) is driven by accessible sensors in portable devices.
• Integrating diverse sensor data is crucial for robust and continuous positioning, especially across indoor and outdoor environments.

Purpose of the Study:

• To develop and evaluate a low-cost multi-sensor platform for seamless indoor-outdoor pedestrian navigation.
• To fuse data from ultra-wideband (UWB) and global navigation satellite systems-inertial navigation system (GNSS-INS) using an extended Kalman filter (EKF).
• To demonstrate the system's capability in providing continuous navigation solutions via a geo-fencing approach.

Main Methods:

• Development of a multi-sensor platform combining UWB and GNSS-INS.
• Implementation of an extended Kalman filter (EKF) for sensor data fusion.
• Utilisation of a geo-fencing algorithm for continuous navigation solution provision.
• Real-time positioning estimation and comparison with ground truth measurements.

Main Results:

• The proposed data fusion algorithm achieved an overall horizontal accuracy of 35 cm and 3D accuracy of 45 cm.
• Performance was validated across 5 distinct measurement campaigns.
• Detailed analysis of the UWB positioning system's environmental behavior was conducted.

Conclusions:

• The developed low-cost multi-sensor platform enables seamless indoor-outdoor pedestrian positioning.
• The EKF-based data fusion approach effectively integrates UWB and GNSS-INS data for continuous navigation.
• The system demonstrates significant potential for enhancing location-based services requiring precise positioning.