WiPIHT: A WiFi-Based Position-Independent Passive Indoor Human Tracking System
Abstract
1. Introduction
- Propose a method to extract human motion trajectory features using CSI by performing amplitude and phase error correction and denoising on raw CSI data, making the CSI data more representative of human activities.
- Utilize only two non-parallel WiFi device links to ensure real-time reconstruction of motion trajectory shapes, regardless of the position, speed, and direction of human movement, even when the relative positions of the TXs and RXs to the human body are unknown. Calculations of initial position and initial motion angle provide absolute trajectory coordinates.
- Implement WiPIHT on regular commercial WiFi devices and conduct extensive experiments and evaluations, validating the efficiency and high precision of the trajectory reconstruction. Evaluation on five test subjects following four different predefined trajectories show that, in a typical indoor environment, WiPIHT achieves a median tracking error of less than 0.3 m in trajectory reconstruction.
2. Related Works
2.1. Non-RF-Based Human Activity Tracking
2.2. RF-Based Human Activity Tracking
3. System Overview
4. CSI Error Correction
4.1. Fresnel Zone and CSI Phase Rotation
4.2. CSI Error Correction and Denoising Based on Amplitude and Phase
5. Position-Independent Feature Extraction
5.1. Position-Independent Real-Time Velocity
5.2. Position-Independent Real-Time Motion Direction
6. Real-Time Trajectory Recovery
6.1. Motion Detection
6.2. Initial Position Estimation
6.3. Trajectory Recovery
Algorithm 1: WiPIHT Trajectory Recovery |
7. Experiment and Evaluation
7.1. Experimental Setup
7.2. Experimental Results
7.2.1. Trajectory Recovery Error
7.2.2. Impact of Movement Speed
7.2.3. Impact of Static Layout
7.2.4. Impact of Transceiver Initial Position
7.2.5. Impact of User Diversity and Preset Trajectory Diversity
7.2.6. Impact of Sample Rate
7.2.7. Impact of Other Dynamic Objects
8. Conclusions and Future Work
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Method | TX-RX Location | Training | Facility | Real Time | Initial Position |
---|---|---|---|---|---|
RSSI | ✓ | high | Commercial WiFi | medium | ✓ |
WiDAR | ✓ | medium | Commercial WiFi | high | ✓ |
IndoTrack | ✓ | ✗ | Dedicated device | high | ✓ |
WiPIHT | ✗ | ✗ | Commercial WiFi | high | ✗ |
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Xu, X.; Che, X.; Meng, X.; Li, L.; Liu, Z.; Shao, S. WiPIHT: A WiFi-Based Position-Independent Passive Indoor Human Tracking System. Sensors 2025, 25, 3936. https://doi.org/10.3390/s25133936
Xu X, Che X, Meng X, Li L, Liu Z, Shao S. WiPIHT: A WiFi-Based Position-Independent Passive Indoor Human Tracking System. Sensors. 2025; 25(13):3936. https://doi.org/10.3390/s25133936
Chicago/Turabian StyleXu, Xu, Xilong Che, Xianqiu Meng, Long Li, Ziqi Liu, and Shuai Shao. 2025. "WiPIHT: A WiFi-Based Position-Independent Passive Indoor Human Tracking System" Sensors 25, no. 13: 3936. https://doi.org/10.3390/s25133936
APA StyleXu, X., Che, X., Meng, X., Li, L., Liu, Z., & Shao, S. (2025). WiPIHT: A WiFi-Based Position-Independent Passive Indoor Human Tracking System. Sensors, 25(13), 3936. https://doi.org/10.3390/s25133936