ViWiTraj: Variational motion tracking in multi-link device-free Wi-Fi sensing under uncertainty

The device-free Wi-Fi sensing has numerous benefits in practical settings, as it obviates the requirement for any dedicated device for sensing and can accomplish sensing on current low-cost Wi-Fi devices. Various methods have been proposed for motion tracking using Angle of Arrival (AoA), Time of Flight (ToF), and Doppler Frequency Shift (DFS) from Wi-Fi signals. However, a statistical model for motion tracking with DFS in multi-link scenarios has yet to be established, and uncertainties like the target's initial position can cause severe performance degradation. To address these challenges, we present an algorithm called ViWiTraj for DFS-based motion tracking in Multi-Link Wi-Fi environments. ViWiTraj incorporates a novel Doppler Frequency Shift (DFS) measurement model in multi-link scenarios that explicitly accounts for uncertainties in receiver positions and initial target location, enabling joint estimation of motion-tracking states and model parameters through structural variational inference. This approach improves Wi-Fi motion tracking usability and precision by reducing sensitivity to parameter uncertainties, improving tracking accuracy in multi-link environments, and decreasing reliance on prior knowledge of the environment and target. We have tested our algorithm in simulated and real-world scenarios with different uncertainty levels, demonstrating superior performance in Multi-Link motion tracking compared to existing methods. ViWiTraj achieves improved accuracy while imposing fewer requirements on prior knowledge of the environment and target, making it more adaptable to diverse real-world applications.