Map-Aided Indoor Navigation with Uncertainty Estimation
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Solution Overview
Problem
Conventional navigation systems, especially those relying on inertial sensors and GNSS, face significant challenges in providing seamless and accurate positioning in indoor environments due to sensor drift and the absence of GNSS signals, and existing map-aided algorithms struggle to handle complex indoor scenarios with multi-level structures and user motion status information effectively.
Innovation Solution
A method and system that utilize offline map matching techniques to enhance navigation solutions by generating and managing multiple hypotheses based on sensor data and map information, allowing for improved position estimation and uncertainty measurement, even in complex indoor environments with unconstrained device mobility and orientation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional SINS uses low cost inertial sensors for positioning, then the system can operate without GNSS signals, but the positioning accuracy degrades significantly due to accumulated sensor drifts and bias
Solution Approach 1:
The patent applies feedback by using map information to constrain and correct the inertial navigation solution. The map-matching process continuously compares the estimated position from inertial sensors with known map features, providing feedback to correct accumulated drift and maintain positioning accuracy in indoor environments where GNSS is unavailable.
Solution Approach 2:
The patent uses preliminary action by pre-processing map information into a constrained model before navigation. The map is processed offline to create a structured representation that can be efficiently used during real-time navigation to constrain the inertial solution, avoiding the need for complex real-time map processing.
2Measurement precision
If PDR accumulates successive displacement from a known starting point to derive position, then the position error accumulates slower than SINS, but the heading error causes skewed path and position estimates inconsistent with building layout
Solution Approach 1:
The patent applies feedback by using map constraints to correct the PDR solution. The map-matching process provides continuous feedback to adjust the estimated trajectory, ensuring that the navigation path remains consistent with the building layout and correcting heading errors that would otherwise cause the path to skew over time.
Solution Approach 2:
The patent uses map information as an intermediary to mediate between the PDR solution and the building layout. The map acts as a reference framework that constrains and guides the PDR trajectory, ensuring consistency with the actual building structure without requiring direct sensor measurements of the building features.
3Reliability
If map information is used to constrain PDR solution to areas indicated as possible routes, then navigation trajectory consistency with building layout is improved, but the system complexity increases due to multiple hypotheses and offline processing
Solution Approach 1:
The patent applies preliminary action by pre-processing map information offline into a constrained model before navigation. This reduces real-time processing complexity by preparing the map data in advance, allowing the system to use pre-computed constraints during navigation without requiring complex real-time map processing or multiple hypothesis generation.
Data Source
AI summary
The navigation solution of a portable device may be enhanced using map information. Sensor data for the portable device may be used to derive navigation solutions at a plurality of epochs over a first period of time. Position information for the device may be estimated at a time subsequent to the first period of time using the navigation solutions. Map information for an area encompassing a current location of the portable device may also be obtained. Multiple hypotheses regarding possible positions of the portable device may be generated using the estimated position information and the map information. By managing and processing the hypotheses, estimated position information for at least one epoch during the first period of time may be updated. An enhanced navigation solution for the at least one epoch may be provided using the updated estimated position information and an uncertainty measure may be derived for the enhanced navigation solution.