3D Indoor Position Estimation Based on a UDU Factorization Extended Kalman Filter Structure Using Beacon Distance and...

Area of Science:

• Robotics and Automation
• Sensor Fusion
• Navigation Systems

Background:

• Global Positioning System (GPS) is effective outdoors, but indoor positioning requires more efficient, reliable, and cost-effective technologies.
• Existing indoor positioning methods include Wi-Fi, Bluetooth, infrared, ultrasound, magnetic, and visual-marker-based systems.
• There is a need for advanced algorithms to improve accuracy and reliability in indoor environments.

Purpose of the Study:

• To design an accurate indoor position estimation algorithm by fusing data from ultrasonic sensors and inertial measurement units.
• To implement and evaluate the algorithm using an extended Kalman filter (EKF) with UDU factorization.
• To achieve centimeter-level precision for indoor positioning applications.

Main Methods:

• Combined raw distance data from ultrasonic sensors (Marvelmind Beacon) with acceleration data from an inertial measurement unit (IMU).
• Utilized an extended Kalman filter (EKF) with UDU factorization for sensor fusion and position estimation.
• Employed a recursive least squares (RLS) method with trilateration for initial position calculation.
• Collected data using the Robot Operating System (ROS) and implemented on a Pixhawk development card.

Main Results:

• The developed algorithm accurately estimates position with centimeter precision.
• The UDU-EKF structure integrated into the embedded system demonstrated faster performance compared to the classical EKF.
• Tests confirmed the algorithm's effectiveness using various configurations of fixed and moving sensors.

Conclusions:

• The proposed algorithm effectively fuses ultrasonic and inertial data for accurate indoor positioning.
• The UDU-EKF approach offers a computationally efficient and precise solution for embedded indoor navigation systems.
• The system achieves centimeter-level accuracy, making it suitable for applications requiring high-precision localization.