Wireless Motion Tracking via Channel State Information
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Solution Overview
Problem
Current motion tracking technologies, such as those using Inertial Measurement Units (IMUs) and radio signals, face challenges with accuracy and robustness due to noise, drift, and the need for specialized hardware, while wireless vital sign monitoring with WiFi signals struggles with low spatial resolution and signal interference in rich-scattering environments.
Innovation Solution
A wireless monitoring system that uses a transmitter and receiver to transmit probe signals through a wireless multipath channel, extracting time series of channel information to accurately track object motion and vital signs, including breathing rate, without the need for dedicated devices or precise hardware installation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Inertial Measurement Units (IMUs) are used for motion tracking, then motion parameters can be measured, but significant errors and drifts occur due to noisy accelerometer readings, magnetometer distortion, and gyroscope integration drift
Solution Approach 1:
The patent replaces the mechanical sensor-based IMU system with a wireless signal-based tracking system. Instead of using physical accelerometers, gyroscopes, and magnetometers that suffer from drift and noise, the system uses wireless channel state information (CSI) to estimate motion parameters, eliminating the fundamental limitations of mechanical sensing devices.
Solution Approach 2:
The patent introduces wireless signals as an intermediary medium to track motion. Rather than directly measuring motion with sensors attached to the object, the system uses the interaction between wireless signals and the moving object to infer motion parameters, providing a non-contact and drift-free measurement approach.
2Measurement precision
If radio signal systems are used for localization and tracking, then target locations can be determined, but the systems require precisely installed Access Points with accurate geometry information, limiting adaptability
Solution Approach 1:
The patent enables the wireless system to self-calibrate and automatically determine the geometry of Access Points through signal interactions, eliminating the need for manual precise installation and measurement of AP positions. The system learns the environmental geometry autonomously, making deployment flexible and adaptable to different venues.
Solution Approach 2:
The patent changes the approach from requiring fixed, pre-configured AP geometry to dynamically adapting to varying AP positions and environmental layouts. The system adjusts its tracking algorithms based on the actual wireless channel characteristics observed in different deployment scenarios, enabling versatile application across diverse environments.
3Device complexity
If commercial off-the-shelf WiFi devices are used for tracking, then system complexity is reduced, but accuracy is limited by frequency bandwidth, antenna amount, and synchronization errors
Solution Approach 1:
The patent extracts and utilizes fine-grained Channel State Information (CSI) parameters from commodity WiFi devices, transforming the limited raw signal data into precise motion tracking measurements. By changing how the available WiFi parameters are processed and interpreted, the system achieves high accuracy without requiring specialized hardware.
Solution Approach 2:
The patent substitutes specialized high-precision tracking hardware with commodity WiFi devices by replacing direct physical measurement mechanisms with wireless signal processing techniques, achieving comparable or superior accuracy while dramatically reducing system complexity and cost.
4Ease of operation
If wireless signals are used for vital sign monitoring in rich-scattering environments, then non-contact monitoring is achieved, but spatial resolution is low and signal interference occurs
Solution Approach 1:
The patent segments the complex wireless channel into multiple independent paths (multipath components), each carrying information about reflections from different objects or body parts. By separating and analyzing individual multipath components, the system achieves high spatial resolution and can distinguish between multiple targets even in rich-scattering environments.
Solution Approach 2:
The patent uses the multipath wireless channel itself as an intermediary that provides detailed spatial information. Rather than treating multipath reflections as interference to be eliminated, the system exploits them as carriers of precise spatial and physiological information, transforming the scattering environment into a useful resource for high-resolution monitoring.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system achieves accurate tracking of motion and vital signs with high spatial resolution, enabling multi-person localization and monitoring in complex environments, improving upon existing technologies by using commodity WiFi devices and eliminating the need for specialized hardware.
Implementation Method 1
transmitting a series of probe signals in a venue through a wireless multipath channel
Implementation Method 2
receiving, through the wireless multipath channel between the transmitter and the receiver, the series of probe signals modulated by the wireless multipath channel and an object moving in the venue
Data Source
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Figure 3A
AI summary
Methods, apparatus and systems for wireless tracking with graph-based particle filtering are described. A described wireless monitoring system comprises a transmitter transmitting a series of probe signals, a receiver, and a processor. The receiver is configured for: receiving the series of probe signals modulated by the wireless multipath channel and an object moving in a venue, and obtaining a time series of channel information (TSCI) of the wireless multipath channel from the series of probe signals. The processor is configured for: monitoring a motion of the object relative to a map based on the TSCI, determining an incremental distance travelled by the object in an incremental time period based on the TSCI, and computing a next location of the object at a next time in the map based on at least one of: a current location of the object at a current time, the incremental distance, and a direction of the motion during the incremental time period.