3D RF Performance Mapping for Aircraft Fuselage Coverage
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Solution Overview
Problem
Existing RF network modeling in indoor environments, such as aircraft, faces challenges due to poorly understood RF characteristics and limitations in representing multi-path propagation issues, making it difficult to reliably communicate within complex metal fuselage environments.
Innovation Solution
A 3-D RF performance mapping system that correlates RF performance data with spatial data generated by a scanner, like LiDAR, to create efficient and rapid identification of communication issues, using an RF receiver mounted proximate to the scanner to capture RSSI and other performance metrics while moving through the environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual testing equipment is placed at various locations to capture RF information, then RF data can be collected, but the process is time consuming and limited in sample size
Solution Approach 1:
The patent replaces manual mechanical testing equipment placement with an automated mobile mapping system that combines RF receivers, GNSS receivers, and inertial measurement units. This system automatically collects RF performance data while moving through the environment, eliminating the need for manual equipment placement at numerous locations and significantly reducing testing time while maintaining measurement accuracy.
Solution Approach 2:
The mobile mapping system integrates multiple functions into a single platform: spatial mapping, RF signal measurement, positioning (GNSS and inertial navigation), and data synchronization. This multi-functional system can collect comprehensive RF performance data across the entire environment in one pass, rather than requiring separate manual testing at each location.
2Productivity
If manual testing is performed at limited locations, then testing can be completed quickly, but possible communication issues in the environment are missed
Solution Approach 1:
The mobile mapping system continuously collects RF performance data throughout its movement through the environment, providing continuous coverage rather than discrete point measurements. This continuous data collection ensures that communication issues are detected across the entire environment, not just at selected test locations, while maintaining high testing efficiency.
Solution Approach 2:
The system uses inertial measurement units and GNSS receivers as intermediary technologies to accurately track the position and orientation of the mobile platform. This enables precise mapping of RF data to spatial locations, ensuring that communication issues are reliably detected and located throughout the entire environment without missing any areas.
3Loss of information
If RF modeling is used to infer RF propagation, then RF characteristics can be estimated, but the model depends highly on geometry and material characteristics that are poorly understood
Solution Approach 1:
The mobile mapping system performs self-calibration and automatic environmental characterization by collecting spatial, inertial, and RF data simultaneously. The system automatically correlates RF performance measurements with precise location and environmental geometry data, eliminating the need for manual input of material characteristics or geometric parameters that are often poorly understood.
Solution Approach 2:
The system uses real-time feedback from inertial measurement units and GNSS receivers to continuously update the position and orientation of the mobile platform. This feedback mechanism enables accurate mapping of RF data to spatial coordinates, allowing the system to build an accurate representation of RF propagation characteristics based on actual measurements rather than theoretical models.
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 quick and efficient identification of RF communication issues by generating 3-D RF performance maps, allowing for optimal placement and configuration of RF transmitters to ensure reliable coverage within complex environments.
Implementation Method 1
A LiDAR scanner that generates time-stamped 3-D spatial data of an environment
Implementation Method 2
An RF receiver located proximate to the scanner that generates RF data for an RF transmitter located within the environment
Data Source
AI summary
Embodiments described herein provide for the generation of 3-D RF performance maps of an environment by correlating RF performance data generated from known locations within the environment with spatial data generated of the environment. One embodiment comprises an apparatus that generates spatial data of an environment in a 3-D coordinate system. The apparatus generates RF performance data for an RF transmitter that is located within the environment. The apparatus identifies 3-D locations of the apparatus within the environment based on the spatial data, identifies RF performance values for the RF transmitter at the 3-D locations based on the RF performance data, and generates a 3-D RF performance map of the environment based on the 3-D locations and the RF performance values.