3D Spatial Tracking via Sensor Fusion
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Solution Overview
Problem
Conventional location tracking systems using Bluetooth Low Energy (BLE) and radio signals are limited to one-dimensional spatial processing, failing to account for the three-dimensional (3D) spatial awareness of devices in environments like malls or stadiums, which is essential for accurate spatial mapping and cross-device interactions.
Innovation Solution
The system fuses BLE signal strength, inaudible acoustic signals, and dead reckoning data from orientation and acceleration sensors to determine 3D spatial mapping of devices, enabling ad-hoc cross-device interactions without the need for external infrastructure or calibration, using commodity mobile devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional BLE signal strength interpolation is used for location tracking, then the system is simple to implement, but the spatial tracking precision is limited to one-dimensional and insufficient for 3D spatial awareness
Solution Approach 1:
The patent combines multiple tracking methods (BLE signal strength, acoustic signals, and dead reckoning) into a unified 3D spatial tracking system. Each method contributes different dimensions of spatial information, and their fusion through sensor fusion algorithms achieves comprehensive 3D tracking precision without requiring any single method to be overly complex
Solution Approach 2:
The system transitions from conventional one-dimensional BLE signal strength tracking to three-dimensional spatial tracking by incorporating acoustic signal arrival time differences and dead reckoning data from orientation and acceleration sensors, adding vertical and angular dimensions to the tracking capability
2Measurement precision
If additional components or cross-device calibration infrastructure is added to achieve accurate 3D tracking, then the tracking accuracy improves, but the ease of operation and deployment deteriorates
Solution Approach 1:
The system uses sensors and components that are already present in commodity mobile devices (BLE radio, acoustic sensors, orientation sensors, acceleration sensors) to perform 3D spatial tracking. No external infrastructure, additional hardware components, or cross-device calibration procedures are required, as each device independently possesses all necessary capabilities
Solution Approach 2:
The patent demonstrates that standard commodity mobile devices can perform multiple functions (BLE communication, acoustic signaling, inertial measurement) required for 3D tracking without specialized hardware, making the system universally deployable across existing device platforms
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
This approach allows for accurate 3D spatial tracking and mapping of devices within a location, enabling efficient file sharing and spatial awareness, improving the suitability of BLE signals for distance tracking and refining spatial context information.
Implementation Method 1
conventional tracking systems interpolate the signal strengths observed for each device, essentially using signal strength as a distance cue
Implementation Method 2
the audio-distance measurement based on acoustic signals and time stamps communicated to and from each identified device
Implementation Method 3
the dead reckoning of each device involves integrating signals associated with orientation and acceleration sensors of each device at the location
Data Source
AI summary
Disclosed is a three-dimensional ad-hoc tracking system and method between two or more devices at a location. The disclosed systems and methods can be implemented on commodity mobile devices with no added components and require no cross-device calibration, in order to track surrounding devices. Such tracking can be achieved by fusing three types of signals: 1) the strength of Bluetooth low energy signals reveals the presence and rough distance between devices; 2) a series of inaudible acoustic signals and the difference in their arrival times produces a set of accurate distances between devices, from which 3D offsets between the devices can be derived; and 3) the integration of dead reckoning from the orientation and acceleration sensors of all devices at a location to refine the estimate and to support quick interactions between devices. The disclosed systems and methods can be implemented by cross-device applications on mobile devices.