MAMPI-UWB-Multipath-Assisted Device-Free Localization with Magnitude and Phase Information with UWB Transceivers.

Area of Science:

• Electrical Engineering
• Computer Science
• Signal Processing

Background:

• Device-free localization (DFL) systems enable tracking without requiring users to carry dedicated devices.
• Existing DFL systems often rely on signal strength measurements and multiple sensors.
• Multipath propagation, typically a challenge, can be leveraged for improved localization accuracy.

Purpose of the Study:

• To propose a novel multipath-assisted device-free localization (DFL) system named MAMPI (Magnitude and Phase Information).
• To utilize ultra-wideband (UWB) channel impulse response (CIR) measurements for extracting multipath components (MPCs).
• To develop and validate a radio propagation model and an error model for DFL measurements.

Main Methods:

• Extraction of multipath components (MPCs) from Decawave DW1000 CIR measurements.
• Development of feature vectors using magnitude and phase differences of MPCs.
• Radio propagation and error model validation.
• Simulation and indoor experimental evaluation of the MAMPI system.

Main Results:

• The MAMPI system effectively extracts MPCs from UWB CIR measurements.
• A validated radio propagation model accurately predicts signal effects based on user position.
• Simulations and experiments demonstrate the system's performance.
• MAMPI achieves a position error probability comparable to conventional DFL systems.

Conclusions:

• The proposed MAMPI system offers an efficient DFL solution by leveraging UWB multipath information.
• The system achieves comparable accuracy to conventional methods while requiring only two sensor nodes, significantly reducing hardware needs.
• This approach demonstrates the potential of using both magnitude and phase information from MPCs for accurate and resource-efficient device-free localization.