Map Vector Constraints for GNSS Location Accuracy
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Solution Overview
Problem
Current navigation systems face challenges in accurately determining the location and direction of travel, especially in environments with limited satellite signals or high GPS uncertainty, where they struggle to reject bad pseudorange and Doppler measurements and adapt to user activity and road conditions.
Innovation Solution
The method involves using map vector constraints, particle seeding, and particle filtering to improve location determination and direction of travel, incorporating Wi-Fi locations and activity context to enhance the accuracy of Global Navigation Satellite System (GNSS) receivers and adapt map-matching processes based on user activity and road conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional GPS positioning is used in environments with limited satellite signals, then the system can operate without additional sensors, but the measurement precision deteriorates due to high GPS uncertainty and inability to reject bad pseudorange and Doppler measurements
Solution Approach 1:
The patent introduces map vector constraints as an intermediary element between GPS measurements and position estimation. These constraints act as a mediator that filters and corrects bad GPS measurements by comparing particle filter results against known road network geometry, thereby improving measurement precision while maintaining system reliability in environments with limited satellite signals
Solution Approach 2:
The patent replaces reliance on purely mechanical/GPS-based positioning with a computational approach using particle filtering and map matching. This substitution transforms the positioning system from one dependent on satellite signal strength to one that uses probabilistic computation and geometric constraints to achieve accurate location determination
2Measurement precision
If particle filtering with map vector constraints is implemented, then the measurement precision improves by rejecting bad measurements, but the device complexity increases due to additional processing requirements
Solution Approach 1:
The patent applies preliminary action by pre-seeding particles on the road network before processing GPS measurements. This preparatory step establishes a structured framework of possible positions and directions along road segments, which simplifies subsequent measurement evaluation and reduces the computational complexity of real-time filtering operations
Solution Approach 2:
The patent segments the continuous road network into discrete map vectors or road segments. This segmentation allows the particle filter to evaluate positions and directions on a finite set of road segments rather than continuous space, reducing computational complexity while maintaining measurement precision through systematic evaluation of discrete possibilities
3Adaptability or versatility
If map-matching processes are adapted based on user activity context, then the adaptability improves for different usage scenarios, but the device complexity increases due to activity detection and context processing
Solution Approach 1:
The patent implements dynamics by making map-matching parameters adaptive rather than static. The system dynamically adjusts particle filter parameters, measurement noise models, and matching thresholds based on detected user activity context such as walking, running, or driving. This dynamic adaptation improves versatility across different usage scenarios while the modular implementation keeps complexity manageable
Solution Approach 2:
The patent creates a universal map-matching framework that handles multiple user activities and environments through a single integrated system. The particle filter architecture universally processes different types of measurements and constraints regardless of whether the user is walking, running, or driving, achieving multi-functionality without requiring separate specialized systems for each activity type
Data Source
AI summary
Systems, methods, and computer program products for determining the location and direction of travel of a mobile device using map vector constraints is disclosed.