Adaptive Positioning System Using Sparse UWB Ranging and Dead Reckoning
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Solution Overview
Problem
Current positioning systems face challenges in providing accurate and reliable position estimation across various environmental conditions, particularly in areas with limited infrastructure and obstructions, and lack the ability to adaptively assess and combine data from multiple sensors for improved accuracy.
Innovation Solution
The Adaptive Positioning System (APS) utilizes a combination of sparse time-of-flight data and dead reckoning, along with Ultra Wide Band (UWB) transceivers and radar depth imagery, to create a modular framework that intelligently fuses and filters data from multiple sensors, including GPS, dead reckoning, and UWB ranging, to provide a highly accurate and reliable positional estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If map matching is used to determine position, then position can be identified when matching characteristics are found, but position determination fails or becomes ambiguous in areas with minimal distinguishing features
Solution Approach 1:
The patent combines map matching with dead reckoning to create a hybrid positioning system. When map matching cannot determine position (e.g., in featureless areas), dead reckoning provides continuous position estimation based on motion sensors, thereby maintaining positioning capability across all environments.
Solution Approach 2:
Dead reckoning serves as an intermediary system that bridges gaps when map matching fails. It provides continuous position estimates during transitions between mapped areas and in featureless regions, ensuring uninterrupted positioning service.
2Adaptability or versatility
If dead reckoning is used to determine position, then position can be continuously estimated independent of environmental conditions, but cumulative sensor errors increase over time
Solution Approach 1:
The system uses map matching as a feedback mechanism to correct dead reckoning drift. When the device enters a mapped area with distinguishing features, map matching provides accurate position references that reset and correct the cumulative errors accumulated by dead reckoning.
Solution Approach 2:
The system pre-processes sensor data through dead reckoning to provide continuous position estimates before accurate position fixes are available. This preliminary positioning allows the device to maintain awareness of its location even when map matching cannot yet determine position.
3Measurement precision
If multiple sensors are used for positioning, then positioning accuracy can be improved, but system complexity increases
Solution Approach 1:
The system dynamically switches between and combines different positioning methods based on environmental conditions and data availability. It adapts the weighting and fusion of map matching and dead reckoning results in real-time, optimizing positioning accuracy without requiring a permanently complex system architecture.
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
The APS effectively mitigates sensor failures and limitations by iteratively evaluating sensor contributions, providing precise and multimodal position estimation even in environments with limited infrastructure or obstructions, and adapts behavior to optimize positioning accuracy.
Implementation Method 1
a time-of-flight module, responsive to the object being within range of one or more transmitters based on the dead reckoning local frame of reference, establishes a conversation with a transmitter to collect range data between the object and the transmitter
Data Source
AI summary
Mobile localization of an object having an object positional frame of reference using sparse time-of-flight data and dead reckoning can be accomplished by creating a dead reckoning local frame of reference, including an estimation of object position with respect to known locations from one or more Ultra Wide Band transceivers. As the object moves along its path, a determination is made using the dead-reckoning local frame of reference. When the object is within a predetermine range of one or more of the Ultra Wide Band transceivers, a “conversation” is initiated, and range data between the object and the UWB transceiver(s) is collected. Using multiple conversations to establish accurate range and bearing information, the system updates the object's position based on the collected data.