Cellular Navigation Error Correction Using EKF and Machine Learning
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Solution Overview
Problem
Existing navigation technologies face inaccuracies when using cellular network signals for positioning due to issues like transmission time imprecision, clock frequency errors, antenna location uncertainties, bandwidth limitations, Doppler shifts, and multipath effects, which are not effectively addressed by previous Assisted GPS (A-GPS) methods.
Innovation Solution
The method involves determining pseudorange and range rate measurements with respect to cellular base stations, using Extended Kalman Filtering (EKF) and Machine Learning (ML) to correct errors, combining these with GNSS/INS sensor data for improved navigation accuracy, even when satellite positioning is unavailable.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cellular network signals are used to augment navigation, then positioning reliability is improved in poor GPS signal conditions, but measurement precision deteriorates due to multiple error sources
Solution Approach 1:
The system performs preliminary error characterization by collecting pseudorange measurements from multiple cellular base stations during periods when GPS signals are available and reliable. These measurements are used to pre-calculate error profiles for each base station, including clock frequency offsets and location inaccuracies, storing them for later correction during GPS-denied operations.
Solution Approach 2:
The system continuously monitors pseudorange measurements from cellular base stations and compares them against expected values derived from GPS positioning data. When discrepancies are detected, the system adjusts error correction parameters in real-time, creating a feedback loop that adapts to changing cellular network conditions and improves measurement precision over time.
2Measurement precision
If GPS signals are used for positioning, then measurement precision is maintained, but reliability deteriorates in urban areas with obstructed line of sight
Solution Approach 1:
The system introduces cellular network infrastructure (base stations and towers) as intermediary positioning elements that can provide location data in environments where direct GPS satellite visibility is blocked. These intermediaries relay positioning information through available signal paths, including reflected and diffracted signals, maintaining positioning capability when direct line-of-sight GPS is unavailable.
Solution Approach 2:
The system merges GPS positioning data with cellular network positioning data into a unified navigation solution. During GPS-denied operations, the system combines pseudorange measurements from multiple cellular base stations with pre-characterized error models to generate accurate position estimates, effectively merging two different positioning modalities into a single robust system.
3Measurement precision
If error correction using GPS data is applied to cellular signals, then measurement precision is improved, but device complexity increases due to additional processing requirements
Solution Approach 1:
The system segments the error correction process into distinct modular components: pseudorange measurement extraction from cellular signals, error profile generation during GPS availability, error application during GPS denial, and position calculation. Each module handles a specific aspect of the correction process, making the overall complex system manageable and maintainable through clear separation of concerns.
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
This approach significantly reduces errors in pseudorange and range rate measurements, enabling reliable and accurate positioning using cellular signals alone, enhancing navigation processing and reducing dependency on GPS signals.
Implementation Method 1
Doppler shift from movement of the computing device which is determining positioning
Implementation Method 2
Imprecision in the time of transmission; Transmitter clock frequency error and drift over time
Data Source
AI summary
A method, non-transitory computer readable medium, and device for correcting for one or more errors when using mobile network communication signals to augment navigation includes determining one or more pseudorange and range rate measurements for a computing device with respect to one or more cellular base stations. One or more of errors in the one or more pseudorange and range rate measurements are obtained which are determined based on previously received satellite positioning or time data. A current position or current time is determined based on the determined one or more pseudorange and range rate measurements and the one or more obtained errors when one of a plurality of states indicates current satellite positioning or timing data is unavailable. The determined current position or the determined current time for the computing device is provided.