Dead Reckoning Navigation Initialization with Sparse Position Fixes
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Solution Overview
Problem
Conventional navigational systems, such as those using GPS or Radio-Frequency based positioning, become ineffective when degraded or unavailable, particularly indoors, where accurate location and heading determination are challenging without frequent updates from external sources like NFC tags or Wi-Fi access points.
Innovation Solution
A method and system utilizing dead reckoning navigation with inertial, magnetic, and optical sensors to provide higher availability and accuracy of position and heading information, even with infrequent updates from sparse positioning sources, leveraging algorithms like Kalman Filter for data blending and correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS or Radio-Frequency based positioning systems are used, then position determination accuracy is improved, but system reliability deteriorates when degraded or unavailable indoors
Solution Approach 1:
The patent introduces dead reckoning as an intermediary navigation method that bridges the gap between external positioning systems (GPS/Wi-Fi) and internal sensor data. When external systems are unavailable, the dead reckoning algorithm uses inertial sensors (accelerometers, gyroscopes) to continuously estimate position and heading, maintaining navigation capability without requiring constant external signals.
Solution Approach 2:
The system dynamically switches between different navigation modes (GPS-based, Wi-Fi-based, dead reckoning) based on signal availability. The navigation system monitors the status of external positioning sources and transitions to alternative methods when signals are degraded or unavailable, ensuring continuous operation with appropriate accuracy levels for each mode.
2Reliability
If dead reckoning navigation is used with sparse positioning updates, then navigation availability is improved, but heading estimation accuracy deteriorates
Solution Approach 1:
The patent implements feedback mechanisms where received position fixes from external sources (NFC tags, Wi-Fi access points) are used to correct and recalibrate the dead reckoning heading estimates. The system continuously refines its heading accuracy by comparing dead reckoning predictions with actual observed positions and adjusting the heading accordingly, allowing long coasting times while maintaining accuracy.
Solution Approach 2:
The system performs preliminary alignment and calibration using initial position fixes to establish an accurate starting heading before dead reckoning begins. This preliminary setup ensures that subsequent heading estimates are built on a solid foundation, reducing cumulative errors during extended navigation segments without frequent updates.
3Measurement precision
If conventional Kalman Filter data blending is used, then position accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent extracts and simplifies the essential functionality of complex multi-dimensional Kalman Filters by implementing a reduced-order filtering approach. Instead of processing all sensor dimensions simultaneously with full covariance matrices, the system uses simplified update equations that maintain position and heading accuracy while significantly reducing computational burden, making the solution suitable for mobile devices.
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
Enables reliable indoor navigation with longer coasting times and lower latency, reducing errors in heading estimation and maintaining navigation accuracy without frequent external position updates, suitable for consumer devices like smartphones.
Implementation Method 1
These navigational systems can include physical sensors such as MEMS devices and the like. Merely by way of example, the MEMS device can include at least an accelerometer
Implementation Method 2
the MEMS device can include at least an accelerometer, a gyroscope
Implementation Method 3
the MEMS device can include at least an accelerometer, a gyroscope, a magnetic sensor
Data Source
AI summary
A method and system for operating a hand-held computer system for navigation. Embodiments of the present invention includes novel improvements to a navigation method and implementation through a device, which can include inertial and/or magnetic field sensors integrated within a hand held device. The method can include using a single-fix method or a dual-fix method. The single fix method includes monitoring travel distance or time for a pre-specified condition and updating the heading from a dead reckoning process based on a first position fix by using a map. The dual-fix method includes obtaining a second position fix and updating the heading based on the difference in displacement vectors from the dead reckoning process based on the first position fix.