Wireless Beacon Localization via Active Tracker Inversion
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Solution Overview
Problem
Existing wireless localization techniques struggle to accurately determine the precise location of wireless beacon devices, especially in environments with limited network coverage, such as indoors or remote areas, and require complex calibration procedures for mobile beacons.
Innovation Solution
Utilizing fixed beacon signal/location maps and active trackers to determine the precise location of mobile beacons through wireless fingerprinting techniques, without requiring mobile beacons to receive wireless signals, by leveraging weighted averages of signal strengths from fixed beacons and active trackers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If mobile beacons are equipped with advanced receiver capabilities to receive and process wireless signals for localization, then localization accuracy improves, but device complexity and cost increase
Solution Approach 1:
Instead of having mobile beacons receive signals from fixed beacons for localization, the patent inverts the approach by having fixed beacons transmit signals that are received by active trackers, and using the known positions of active trackers to determine mobile beacon locations through signal strength analysis. This eliminates the need for complex receivers in mobile beacons while maintaining localization accuracy.
Solution Approach 2:
The patent introduces active trackers as intermediary devices with known positions that receive signals from fixed beacons and transmit this information to the server. These intermediaries enable the localization of mobile beacons without requiring the mobile beacons themselves to have advanced receiving capabilities, thus resolving the contradiction between accuracy and device complexity.
2Measurement precision
If complex calibration procedures are implemented for mobile beacons to improve localization precision, then measurement accuracy improves, but ease of operation deteriorates
Solution Approach 1:
The system performs self-calibration by automatically determining the positions of active trackers through signal strength analysis and using these determined positions to localize mobile beacons. The server automatically processes the calibration data and updates the beacon signal/location maps without requiring manual intervention, thus improving ease of operation while maintaining precision.
Solution Approach 2:
The patent performs preliminary calibration by establishing beacon signal/location maps that store the relationships between signal strengths and positions of active trackers before actual localization begins. This preliminary action creates a reference framework that simplifies subsequent localization operations and eliminates the need for complex real-time calibration procedures.
3Measurement precision
If GPS-based techniques are used for location determination, then geographical location accuracy improves, but adaptability to indoor and remote areas without network coverage deteriorates
Solution Approach 1:
The patent transitions from GPS-based geographical coordinate systems to a local relative positioning system based on signal strength measurements and beacon locations. This dimensional change from global to local coordinate space enables operation in indoor and remote areas where GPS signals are unavailable, while maintaining localization precision through the beacon-based reference framework.
Data Source
AI summary
A system described herein may determine, based on wireless metrics associated with wireless signals transmitted by a first set of devices, a first reference map associated with a particular space, such as a warehouse, a facility, or the like. The system may determine, based on the first reference map and further based on wireless metrics associated with wireless signals transmitted by the first set of devices and received by a second set of devices, a second reference map associated with the particular space; determine, based on the second reference map and further based on wireless metrics associated with wireless signals transmitted by a third set of devices and received by the second set of devices, locations within the particular space of the third set of devices; and output information indicating the locations, within the particular space, of the third set of devices.