Road User Localization Using GNSS Gap Prediction
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Solution Overview
Problem
Conventional GNSS-based methods for determining relative positions between road users, such as vehicles, suffer from inaccuracies due to non-line-of-sight (NLOS) satellite conditions, leading to gaps in positioning data and unstable estimation results, especially in dynamic environments, and precise systems like DGPS or RTK are too expensive for widespread use.
Innovation Solution
Implementing a 'memory function' or 'prediction function' to fill gaps in pseudorange measurements and matrix calculations, using historical data and motion models to improve the accuracy and stability of relative position estimation, even with low-cost GNSS receivers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a low-cost GNSS receiver is used to determine relative positions, then the system cost is reduced, but the positioning accuracy deteriorates to only a few meters
Solution Approach 1:
The patent introduces an intermediary processing system that receives positioning data from low-cost GNSS receivers and applies correction algorithms. This intermediary layer processes the raw inaccurate data through mathematical models and historical data analysis to produce improved relative position estimates, effectively mediating between the low-cost hardware and the requirement for high positioning accuracy.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring positioning accuracy and using historical data to refine future estimates. The correction algorithm incorporates feedback from previous positioning results and adjusts subsequent calculations to compensate for NLOS conditions, thereby progressively improving accuracy despite using low-cost receivers.
2Measurement precision
If precise systems like DGPS or RTK are used to improve positioning accuracy, then measurement precision is improved, but the system cost becomes too expensive for widespread use
Solution Approach 1:
The patent creates a virtual copy of the expensive precise positioning system's output by using computational algorithms that replicate the accuracy benefits without requiring the expensive hardware. The correction algorithm mimics the effect of DGPS/RTK by processing low-cost GNSS data through mathematical models that emulate the results of expensive reference systems.
Solution Approach 2:
The invention replaces the mechanical/expensive physical infrastructure of DGPS or RTK systems with a software-based computational approach. Instead of requiring expensive reference stations and specialized hardware, the system uses algorithmic processing and historical data to achieve similar positioning accuracy, substituting physical infrastructure with information processing.
3Adaptability or versatility
If the PRDD-based approach is used to determine relative positions, then positioning can be achieved with available satellites, but gaps in positioning data occur due to NLOS conditions causing unstable estimation
Solution Approach 1:
The system performs preliminary actions by pre-processing and storing historical positioning data before actual positioning events occur. This historical data is prepared in advance and used to create correction models that can be applied when NLOS conditions cause data gaps, allowing the system to anticipate and compensate for potential instability rather than reacting to it after it occurs.
Solution Approach 2:
The patent implements beforehand cushioning by using historical data and correction algorithms to compensate for future NLOS conditions. The system builds a buffer of knowledge from past positioning experiences that cushions against the impact of future data gaps caused by satellite blockage, maintaining estimation stability even when current measurements are unavailable.
Data Source
AI summary
A method for localizing a first road user includes receiving a first set of positioning data obtained by a first Global Navigation Satellite System (GNSS) receiver located at the first road user. The method includes receiving second sets of positioning data associated with corresponding second road users. Each second set of positioning data is obtained by a corresponding second GNSS receiver. The method includes, for each second road user, determining a relative position of the second road user with respect to the first road user, based on the first set of positioning data and a corresponding second set of positioning data. Determining the relative position includes evaluating a set of parameters determined based on the first and second sets of positioning data and, in response to one or more parameters being determined as missing, replacing the missing one or more parameters by one or more replacement parameters respectively.