Performance Analysis of ToA-Based Positioning Algorithms for Static and Dynamic Targets with Low Ranging Measurements

Area of Science:

• Engineering
• Computer Science
• Robotics

Background:

• Indoor Positioning Systems (IPSs) are crucial for emergency responders operating in harsh, unstructured environments.
• Ultra-wideband (UWB) technology offers robust signaling, through-wall propagation, and high-resolution ranging for IPSs.
• Challenges include low UWB signal availability and non-line-of-sight (NLOS) conditions during emergency missions.

Purpose of the Study:

• To evaluate the performance of four distance-based positioning algorithms using a commercial off-the-shelf (COTS) UWB transceiver.
• To compare algorithms based on accuracy, precision, and root mean square error (RMSE) under various conditions.
• To assess the impact of NLOS conditions and human body obstruction on positioning accuracy.

Main Methods:

• Performance assessment of Analytical, Least Squares, Taylor Series, and Extended Kalman Filter (EKF) algorithms.
• Utilized a COTS UWB transceiver with three ranging measurements.
• Evaluated algorithms in diverse environments (atrium, lab) for static and mobile devices.
• Implemented a NLOS identification and error mitigation algorithm.

Main Results:

• The Extended Kalman Filter (EKF) algorithm generally outperformed other methods across tested scenarios.
• Positioning accuracy and precision were influenced by environmental propagation conditions and device mobility.
• The human body's presence and NLOS conditions significantly impacted ranging measurements and overall accuracy.
• The EKF's performance was constrained by the low measurement rate inherent in the UWB system.

Conclusions:

• The EKF is a robust choice for UWB-based indoor positioning for emergency responders, especially with NLOS mitigation.
• Further research is needed to address the limitations imposed by low UWB signal rates for real-time applications.
• Optimizing UWB deployment strategies and enhancing signal processing are key for reliable emergency response IPSs.