Indoor Navigation Map Matching Error Correction
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Solution Overview
Problem
Existing indoor navigation systems face challenges in accurately detecting complex events due to disparate handling of sensor events, leading to errors in user position and heading estimation.
Innovation Solution
The use of map-based constraints, such as physical objects like walls and corridors, to augment dead-reckoning navigation systems by intelligently blending map data with inertial and other navigation sources, thereby limiting error growth and refining user position estimates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If discrete motion detectors are used to recognize user state, then basic motion detection is achieved, but complex event detection becomes difficult due to disparate handling of sensor events
Solution Approach 1:
The patent merges multiple discrete motion detector readings into a unified navigation state representation. By combining accelerometer and gyroscope data into a cohesive user state model constrained by map features, the system transforms disparate sensor events into integrated navigation information, enabling reliable complex event detection without proportionally increasing device complexity
Solution Approach 2:
The patent introduces map feature constraints as an intermediary between raw sensor data and navigation output. These constraints act as a mediator that processes and contextualizes sensor events, transforming them into meaningful navigation states. The map constraints serve as an intermediate layer that resolves ambiguities in sensor data and enables sophisticated event detection while keeping the core sensor handling relatively simple
2Reliability
If dead-reckoning positioning is used for indoor navigation, then navigation functionality is provided, but error growth occurs in user position and heading estimates
Solution Approach 1:
The patent implements feedback by continuously comparing dead-reckoning position estimates with map feature constraints. When the estimated position diverges from plausible locations defined by map constraints (such as walls, corridors, or room boundaries), the system corrects the position estimate. This feedback mechanism maintains measurement precision by constantly validating and correcting drift in the dead-reckoning navigation
Solution Approach 2:
The patent changes the parameters of the navigation state by incorporating map constraint information into the position and heading estimates. Instead of relying solely on inertial measurements that accumulate error, the system adjusts the navigation parameters (position, heading, orientation) based on map constraint violations. This parameter adjustment reverses error growth by realigning the estimate with known spatial relationships in the environment
Data Source
AI summary
A computer-implemented method for determining an estimated user location, implemented in a computing system programmed to perform the method includes receiving a map database associated with a geographic location including a plurality of map features, determining an estimated first user location within the geographic location, receiving a first plurality of physical perturbations from a plurality of physical sensors in response to physical perturbations of the computing system, determining an estimated second user location within the geographic location in response to the estimated first user location and to the first plurality of physical perturbations, determining a modified estimated second user location in response to the estimated second user location and to at least one map feature from the plurality of map features, and providing in the computer system, an indication of the modified estimated second user location with regards to the geographic location.