Radar-Based 3D Indoor Mapping via WiFi Signal Reflection
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Solution Overview
Problem
Current indoor mapping systems face challenges such as inaccurate positioning without GPS, high costs due to the need for multiple sensing units, and limited ability to provide three-dimensional images or visual representations of indoor environments, which hinders efficient spatial information gathering and usage in planning and navigation.
Innovation Solution
A computer-implemented method and system using radar technology to continuously scan and update a three-dimensional map of an environment by transmitting and receiving radar signals, measuring signal reflections, and classifying detected objects based on their features, enabling real-time construction and updating of a 3D voxels map with associated event records and statistics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS-based positioning is used for indoor mapping, then outdoor mapping accuracy is improved, but indoor mapping becomes impossible or inaccurate due to poor GPS signal availability
Solution Approach 1:
The system transitions from GPS-based positioning (outdoor parameter) to WiFi signal-based positioning (indoor parameter). By changing the positioning parameter from satellite signals to local wireless signals, the system maintains positioning accuracy across both indoor and outdoor environments.
Solution Approach 2:
The invention replaces the GPS satellite-based positioning system with a local WiFi infrastructure-based system. This substitution enables indoor mapping by using available WiFi signals instead of unavailable satellite signals, while maintaining positioning functionality.
2Measurement precision
If multiple sensing units are deployed for accurate indoor mapping, then measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The system uses a single mobile device that performs multiple functions: positioning, environment scanning, and data collection. By making the mobile device universal, the system eliminates the need for multiple dedicated sensing units while maintaining mapping accuracy.
Solution Approach 2:
The mobile device uses its own built-in sensors (accelerometer, gyroscope, WiFi receiver) to perform positioning and mapping tasks. This self-service approach eliminates the need for external sensing infrastructure, reducing system complexity while maintaining functionality.
3Loss of information
If visual image technologies are used for mapping, then detailed spatial information is obtained, but privacy concerns and inability to penetrate obstacles arise
Solution Approach 1:
The system replaces visual image-based mapping with radio wave-based WiFi signal mapping. Radio waves can penetrate obstacles like glass and thin walls that block light, and the system processes signal data rather than visual images, reducing privacy concerns while maintaining spatial information completeness.
Solution Approach 2:
The system changes the detection parameter from visual intensity (light reflection) to radio signal strength (WiFi reception). This parameter change enables detection through obstacles and reduces privacy intrusion since signal strength data does not reveal visual information about the environment or occupants.
4Quantity of substance
If existing indoor mapping systems are used, then basic 2D positioning is achieved, but three-dimensional mapping and visual representation capabilities are limited or unavailable
Solution Approach 1:
The system transitions from 2D positioning (floor plans) to 3D mapping by incorporating vertical dimension data from barometric pressure sensors and multi-floor WiFi signal analysis. This dimensional expansion enables comprehensive spatial mapping while maintaining accuracy through integration of multiple sensor data sources.
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 provides accurate, cost-effective, and privacy-friendly three-dimensional mapping of indoor environments, capable of detecting objects and tracking motion patterns, even in obstructed or low-visibility conditions, enhancing navigation and spatial planning.
Implementation Method 1
A computer-implemented method and system using radar technology to continuously scan and update a three-dimensional map of an environment by transmitting and receiving radar signals
Implementation Method 2
measuring signal reflections
Data Source
AI summary
Systems and methods thereof configured for mapping an environment, comprising: continuously scanning, via at least one transmit/receive module, the environments volume for detecting objects, the transmit/receive module is configured to transmit signals and receive their reflection; measuring the location of the objects' reflected signals and optionally their strength, via at least one acquisition module and at least one processor; and constructing a real-time updated three-dimensional (3D) voxels' map of the environment; and associating for each voxel a time record of events and optionally their respective event features; wherein each event comprises at least the voxel's detected presence of signal/s.