Collaborative Drone Localization Using Confidence-Weighted Sensor Fusion
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Solution Overview
Problem
GPS positioning is unreliable in urban areas due to multipath errors and other environmental factors, leading to inaccurate location calculations, which can affect navigation, autonomous driving, and location-based services.
Innovation Solution
A collaborative localization system that uses multiple mobile devices to combine various localization techniques such as signal-based ranging, object-based ranging, triangulation, and trilateration, along with peer-to-peer communication and confidence level analysis, to enhance positioning accuracy and consistency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS is used for positioning in urban areas, then location information can be obtained, but accuracy deteriorates due to multipath errors and signal obstruction
Solution Approach 1:
The patent combines multiple positioning techniques (GPS, Wi-Fi, cellular, sensor-based methods) into a unified positioning system. The server aggregates location data from various sources and techniques to determine device position, ensuring accurate positioning even when GPS alone is unreliable due to multipath errors or signal obstruction in urban environments.
Solution Approach 2:
The system dynamically changes positioning parameters by selecting different positioning techniques based on environmental conditions. When GPS accuracy deteriorates in urban areas, the system transitions to alternative techniques such as Wi-Fi triangulation or sensor-based dead reckoning, adjusting the positioning approach to maintain measurement precision under varying conditions.
2Reliability
If multiple positioning techniques are combined to improve accuracy, then positioning reliability improves, but system complexity increases
Solution Approach 1:
The patent introduces a server as an intermediary that centralizes the complex task of integrating multiple positioning techniques. Individual devices send raw positioning data to the server, which then aggregates and processes information from multiple sources using various techniques. This mediator approach allows multiple positioning methods to be combined reliably while preventing excessive complexity at the device level.
Data Source
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AI summary
An apparatus is configured to perform a method for collaborative localization of multiple devices in a geographic area including receiving global localization data originating with one or more neighboring devices, receiving local localization data originating with a mobile device, determining a first confidence level from the local localization data, determining a second confidence level from the global localization data, and performing, by a processor, a collaborative localization calculation for the mobile device based on the first confidence level and the second confidence level.