Aircraft Cabin Object Localization Through Wireless Signal Propagation
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Solution Overview
Problem
Current indoor localization methods for vehicle cabins require additional equipment, which adds weight and certification challenges, necessitating simpler, cost-effective solutions.
Innovation Solution
Utilize existing wireless communication infrastructure in vehicle cabins, such as aircraft, to passively locate objects by analyzing signal propagation data from wireless signals using machine learning, without additional electronics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If additional equipment is installed for indoor localization, then localization functionality is achieved, but weight and certification complexity increase
Solution Approach 1:
The wireless access points serve dual purposes: providing wireless communication infrastructure and enabling object localization through signal propagation analysis. By making the access points multi-functional, the system achieves localization capability without adding separate dedicated localization equipment, thus avoiding the weight penalty of additional hardware.
Solution Approach 2:
The existing wireless communication infrastructure serves itself by using its transmitted signals for both communication and localization purposes. The signal propagation data collected by the access points is analyzed to determine object positions, allowing the system to perform localization without requiring external or additional specialized equipment.
2Reliability
If additional equipment is installed for indoor localization, then localization functionality is achieved, but system complexity and certification requirements increase
Solution Approach 1:
The wireless access points are designed to perform both wireless communication and localization functions. This multi-functionality reduces system complexity by eliminating the need for separate localization hardware and simplifies certification processes since the access points are already certified for communication use.
Solution Approach 2:
The localization function is merged with the existing wireless communication infrastructure. By combining these functions into a single system rather than having separate components, the overall system complexity is reduced and fewer separate certifications are required.
3Measurement precision
If signal propagation data is analyzed using machine learning, then object localization accuracy is improved, but computational requirements increase
Solution Approach 1:
Machine learning models serve as intermediaries that process signal propagation data to extract localization information. These models are trained offline and deployed for inference, enabling accurate localization while managing computational energy requirements through efficient model design and preprocessing of signal data.
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 object localization without extra equipment, reducing weight and certification burdens, and enhancing cabin management efficiency by detecting and tracking objects like luggage or safety equipment.
Implementation Method 1
acquire signal propagation data of wireless signals transmitted over the wireless communication network along multiple propagation paths
Data Source
AI summary
A system for object localization in an indoor environment, such as a passenger cabin of a vehicle or an aircraft, includes a wireless communication infrastructure to facilitate wireless communication within the indoor environment via a wireless communication network and including at least one wireless access point to provide user devices access to the wireless communication network within the indoor environment. The wireless access point is adapted to acquire signal propagation data of wireless signals transmitted over the wireless communication network along multiple propagation paths. A computing element is configured to analyze the signal propagation data and extract localization data from the signal propagation data, the localization data specifying the position of objects located within the indoor environment.