Sensor-Fusion Indoor Localization From Acceleration Events
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Solution Overview
Problem
Existing localization techniques, such as GPS and cellular networks, struggle with accuracy in indoor environments, particularly in complex commercial buildings, and are unreliable during network failures.
Innovation Solution
Utilizing a user device's sensors, like accelerometers and gyroscopes, to detect acceleration and deceleration events, combined with a location server that processes time elapsed and sensor data to determine position within indoor environments, leveraging architectural plans and crowdsourced data for precise positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS and cellular networks are used for localization, then outdoor localization can be achieved, but indoor localization accuracy deteriorates
Solution Approach 1:
The patent introduces an intermediary system consisting of sensor fusion processing units and architectural plan databases that mediate between raw sensor data and localization results. The system uses accelerometers, gyroscopes, and magnetic sensors as intermediaries to capture movement patterns, while architectural plans serve as intermediary reference frameworks for mapping sensor observations to physical locations, thereby enabling accurate indoor localization without direct satellite or cellular signal dependency
Solution Approach 2:
The patent replaces the traditional mechanical/electromagnetic signal-based localization systems (GPS satellites and cellular towers) with an inertial measurement system. Instead of relying on external electromagnetic signals that penetrate poorly through building materials, the system uses onboard accelerometers and gyroscopes to mechanically detect movement, combining this data with architectural plans to substitute the signal-based localization approach with a sensor-fusion-based approach that works independently of external signals
2Measurement precision
If sensor fusion is used to determine position, then localization accuracy improves, but device complexity increases
Solution Approach 1:
The patent segments the complex localization system into distinct functional modules: sensor fusion processing units that handle specific sensor types (accelerometers, gyroscopes, magnetic sensors), an architectural plan database that stores reference information, and a position determination module that integrates all inputs. This segmentation allows each component to be optimized independently and simplifies the overall system architecture by dividing the complex fusion process into manageable stages
Solution Approach 2:
The patent creates a universal localization system where a single sensor fusion processing unit can handle multiple sensor types (accelerometers, gyroscopes, magnetic sensors) and combine their data for position determination. The system uses the same processing framework for both indoor and outdoor environments, with the position determination module adapting its algorithms based on the available sensor data and environmental context, thereby reducing overall system complexity through multi-functionality
3Speed
If real-time sensor data processing is performed, then localization responsiveness improves, but computational energy consumption increases
Solution Approach 1:
The patent implements periodic action by processing sensor data at specific intervals rather than continuously. The system updates position estimates based on detected movement events and architectural landmark references, performing computational fusion operations only when new sensor data becomes available or when the device transitions between indoor and outdoor environments. This periodic processing approach maintains localization responsiveness while significantly reducing peak computational energy consumption compared to continuous real-time processing
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
Enhances indoor localization accuracy by determining distance and direction of travel, enabling precise mapping and navigation within buildings using sensor fusion and environmental data.
Implementation Method 1
A combination of sensors including an accelerometer that is configured to detect an acceleration event and a deceleration event
Implementation Method 2
Additional sensors such as a gyroscope, magnetic sensors, inertial sensors, optical sensors, and/or other types of sensors for determining, for example, the direction of travel
Data Source
AI summary
Techniques for locating a user device in an indoor environment include receiving an indication of an acceleration event at a start position and a deceleration event associated with the user device. Based at least on the amount of time elapsed between the acceleration event and the deceleration event, a traveled distance of the user device may be determined. Additionally, sensor data collected from the user device between the acceleration event and the deceleration event may be used to determine the direction of travel of the user device. Following the determination of the traveled distance and the direction of travel, a finish position relative to the start position of the user device in the indoor environment may be mapped using an architectural plan associated with the indoor environment.