Multilevel Altitude Maps for Indoor Positioning
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Solution Overview
Problem
Current indoor positioning technologies face challenges in achieving accurate 2-3 m horizontal positioning and 100% floor detection due to limitations in signal penetration and infrastructure requirements, especially in multilevel structures, and existing solutions are not scalable or cost-effective for widespread deployment.
Innovation Solution
A method for creating and updating altitude maps using crowd-sourced data from mobile devices, which combines absolute and relative altitude information to determine accurate altitude estimates, allowing for the detection of multilevel structures and improving GNSS and barometer altitude estimation without external data, using algorithms like the Rauch-Tung-Striebel smoother and clustering approaches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional satellite and cellular positioning technologies are used for indoor positioning, then global coverage is achieved, but positioning accuracy deteriorates to unacceptable levels (cannot achieve 2-3 m accuracy)
Solution Approach 1:
The patent introduces radio maps as an intermediary data structure that pre-characterizes the radio propagation environment indoors. Instead of relying on satellite signals that cannot penetrate walls, the system uses pre-measured radio signal characteristics (RSSI, ToF) stored in radio maps to determine position, achieving 2-3m accuracy without direct satellite signal penetration
Solution Approach 2:
The patent creates a virtual copy of the indoor radio environment through radio maps that store pre-measured signal characteristics. This virtual representation allows the system to determine position by comparing current signal measurements against the stored map data, replicating the functionality of satellite positioning within indoor environments where direct signals are unavailable
2Measurement precision
If new infrastructure (pseudolites, beacons, tags) is deployed for indoor positioning, then positioning accuracy improves to 2-3 m, but deployment cost and complexity increase significantly
Solution Approach 1:
The patent makes existing consumer device radio transceivers (Wi-Fi, Bluetooth) perform dual functions: their original communication purposes and positioning measurements. By using these existing components for radio map creation and positioning, the system achieves 2-3m accuracy without deploying dedicated positioning infrastructure like pseudolites or beacons
Solution Approach 2:
The system enables consumer devices to self-generate positioning data by using their own radio transceivers to measure signal characteristics and contribute to radio map creation. This crowd-sourced approach allows the infrastructure to build itself using existing device capabilities, eliminating the need for separate deployment of positioning infrastructure
3Area of stationary object
If manual exhaustive radio surveying is performed to create coverage maps, then positioning coverage reaches 100%, but time and cost requirements become prohibitive
Solution Approach 1:
The patent performs preliminary radio environment characterization by having consumer devices automatically measure and store radio signal characteristics in radio maps during normal operation. This pre-characterization of the radio environment enables rapid positioning without requiring time-consuming manual surveying when deployment is needed
Solution Approach 2:
The system continuously updates and refines radio maps using ongoing measurements from consumer devices during normal operation. This continuous data collection maintains 100% coverage without requiring periodic manual re-surveying, as the useful action of devices operating in the environment simultaneously builds and maintains the positioning infrastructure
4Reliability
If multiple positioning technologies are integrated to achieve 100% floor detection, then detection reliability improves, but system complexity and integration difficulty increase
Solution Approach 1:
The patent merges radio map-based positioning with barometer altitude estimation into a unified 3D positioning system. By combining horizontal position from radio signals with vertical floor information from barometric pressure, the system achieves 100% floor detection capability while using a single integrated approach rather than managing multiple separate technology stacks
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 enables the creation of detailed altitude maps that support accurate indoor positioning by automatically learning multilevel structures, enhancing the reliability of altitude estimation and positioning systems, and reducing the need for extensive infrastructure deployment.
Implementation Method 1
a barometer may provide high-resolution pressure measurements which can be used to estimate altitude changes
Implementation Method 2
determining altitude estimates from the altitude information, wherein the determining of the altitude estimates comprises correcting the altitude estimates based on altitude values of single level sub-sections of the altitude map
Data Source
Figure 1
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AI summary
The invention relates to a method, performed by at least one apparatus. The method comprises obtaining sample measurements at least in part comprising altitude information and observed in an area at least in part represented by an altitude map, the altitude map comprising sub-sections representing respective sub-areas of the area; The method further comprises determining altitude estimates from the altitude information. The method further comprises updating one or more altitude estimate distributions associated with respective sub-sections of the altitude map based on the determined altitude estimates. The method further comprises determining, for one or more sub- sections of the altitude map, whether a respective sub-section of the altitude map represents a single level sub-area or multilevel sub-area, based on respective altitude estimate distributions associated with respective sub-sections of the altitude map.