Localization in Structured Environments with UWB Devices without Acceleration Measurements, and Velocity Estimation...

Area of Science:

• Robotics and Automation
• Signal Processing
• Navigation Systems

Background:

• Global Positioning System (GPS) signals are unreliable in indoor or obstructed environments.
• Traditional localization systems often require accelerometer data, increasing complexity and potential error sources.
• Accurate real-time velocity and position estimation is critical for autonomous systems.

Purpose of the Study:

• To propose a novel estimation scheme for velocity and position in Ultra-Wideband (UWB) range-based localization systems.
• To address limitations of existing systems, specifically in GPS-denied environments and the need for accelerometer data.
• To compare the performance of a designed Kalman-Bucy filter with a particle filter for velocity estimation.

Main Methods:

• Development of a UWB range-based localization scheme.
• Design of a Kalman-Bucy filter for velocity estimation.
• Experimental comparison of Kalman-Bucy filter and particle filter.
• Validation through experimental tests on a developed test setup.

Main Results:

• The proposed UWB localization scheme effectively estimates velocity and position without GPS or accelerometers.
• The Kalman-Bucy filter demonstrates viable performance for velocity estimation in localization contexts.
• Experimental comparisons highlight the features and applicability of both Kalman-Bucy and particle filters.
• The developed test setup validates the proposed approach's effectiveness.

Conclusions:

• The novel UWB localization scheme offers a robust solution for environments where GPS is unavailable or unreliable.
• The system successfully performs localization without requiring accelerometer measurements.
• The Kalman-Bucy filter presents a suitable alternative for velocity estimation within this UWB localization framework.