The Indoor Localization and Tracking Estimation Method of Mobile Targets in Three-Dimensional Wireless Sensor...

Area of Science:

• Robotics and Wireless Sensor Networks
• Indoor Localization Systems
• 3D Positioning Technologies

Background:

• Traditional indoor localization in wireless sensor networks (WSNs) faces signal obstruction from obstacles.
• 3D localization systems offer improved signal transmission via line of sight (LOS), but require new positioning methods.
• Existing localization techniques are often incompatible with 3D deployment modes.

Purpose of the Study:

• To develop novel methods for self-localization and calibration of beacons in 3D indoor environments.
• To enhance the accuracy and reliability of indoor localization systems using wireless sensor networks.
• To address the limitations of traditional localization methods in non-planar WSN deployments.

Main Methods:

• Self-localization of ceiling-mounted beacons using the Cayley-Menger determinant.
• Differential sensitivity analysis (DSA) for eliminating measurement errors during data fusion.
• Calibration of beacon locations using a mobile robot with H∞ filter and strong tracking filter (STF).
• Optimal node selection based on geometric dilution precision (GDOP).
• GDOP-based weighting estimation method (GWEM) for target positioning.

Main Results:

• The strong tracking filter (STF) demonstrated superior beacon location calibration compared to EKF and H∞ filter.
• The proposed GDOP-based weighting estimation method (GWEM) achieved centimeter-level precision in 3D environments.
• The optimal node selection scheme effectively identified beacon subsets minimizing GDOP for enhanced accuracy.

Conclusions:

• The developed methods provide a robust solution for accurate 3D indoor localization in WSNs.
• The combination of STF for calibration and GWEM for positioning offers significant improvements in localization precision.
• This research advances the capabilities of WSNs for high-accuracy positioning in complex indoor settings.