Passive Wireless Tracking Using Channel Signatures Indoors
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Solution Overview
Problem
Existing indoor tracking systems face limitations such as privacy concerns, poor performance in lighting conditions, requirement for specialized hardware, and complexity, especially when using WiFi, and often necessitate a dedicated tracking device.
Innovation Solution
A method and system for passive wireless tracking using wireless signals, employing a transmitter and receiver to generate a time series of channel information (TSCI) based on motion, extracting features like proximity, motion statistics, and spatial features to estimate object location and generate a trajectory without requiring the transmitter or receiver to move with the object.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vision-based tracking systems are used, then tracking capability is achieved, but privacy is invaded and performance fails in poor lighting conditions
Solution Approach 1:
The patent replaces vision-based optical tracking with wireless signal-based tracking using WiFi channel state information. This substitution eliminates dependency on lighting conditions and avoids privacy intrusion by tracking objects through radio wave interactions rather than visual capture, maintaining reliability across diverse environmental conditions.
Solution Approach 2:
The patent changes the fundamental tracking parameter from optical field measurements (vision) to electromagnetic field characteristics (wireless channel state information). By monitoring changes in channel state information caused by object motion, the system achieves tracking without requiring visible light, thereby resolving the lighting dependency issue while maintaining continuous tracking capability.
2Reliability
If acoustic tracking systems are used, then tracking capability is achieved, but performance is degraded by background noise
Solution Approach 1:
The patent substitutes acoustic wave-based tracking with electromagnetic wave-based tracking using wireless signals. This replacement eliminates susceptibility to acoustic background noise while maintaining the ability to detect object motion through signal interactions, achieving reliable tracking in noisy environments.
3Reliability
If infrared tracking systems are used, then tracking capability is achieved, but line of sight is required which limits functionality
Solution Approach 1:
The patent replaces infrared optical tracking with wireless signal-based tracking. Wireless signals can penetrate and diffract around obstacles, enabling tracking without direct line of sight between transmitter and receiver. This substitution maintains tracking capability while significantly improving adaptability to various spatial configurations and obstacle conditions.
4Reliability
If radar-based tracking systems are used, then tracking capability is achieved, but expensive specialized hardware and limited coverage area are required
Solution Approach 1:
The patent leverages the universality of WiFi infrastructure, using existing wireless communication devices for dual purposes: both data communication and object tracking. This eliminates the need for specialized radar hardware while extending coverage area to wherever WiFi signals are present, making the system both cost-effective and scalable.
Solution Approach 2:
The patent enables tracking functionality using the wireless communication system's own infrastructure without requiring separate dedicated tracking hardware. The WiFi network serves itself by utilizing its transmitted signals and channel characteristics for both communication and sensing purposes, reducing overall system complexity and cost.
5Ease of manufacture
If WiFi-based tracking systems are used, then cost-effectiveness and ubiquity are achieved, but system complexity and training requirements increase
Solution Approach 1:
The patent implements a self-service approach where the tracking system automatically calibrates and adapts to the specific WiFi environment without requiring manual training or configuration. The system autonomously learns channel characteristics and object signatures, eliminating the need for extensive training while maintaining cost-effectiveness using standard WiFi infrastructure.
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
Enables accurate and scalable indoor tracking without dedicated devices, leveraging ubiquitous wireless signals to track objects passively and generate trajectories effectively.
Implementation Method 1
the received wireless signal differs from the transmitted wireless signal due to the wireless channel and a motion of an object in the venue
Data Source
AI summary
Examples for performing wireless tracking are described. In one example, a described method comprises: transmitting, by at least one transmitter, a wireless signal through a wireless channel of a venue; receiving, by a receiver, the wireless signal, wherein the received wireless signal differs from the transmitted wireless signal due to the wireless channel and a motion of an object in the venue, wherein neither the at least one transmitter nor the receiver moves with the object; obtaining a time series of channel information (TSCI) of the wireless channel in a time window based on the received wireless signal; generating a plurality of features based on the TSCI over the time window; obtaining a signature map of the venue, wherein each location on the signature map is assigned one or more location signatures representing unique features associated with the location when there is any object at the location; identifying, for each time stamp in the time window, an estimated location of the object in the venue based on the signature map and the plurality of features, and generating a trajectory of the object in the venue over the time window based on the estimated locations of the object.