Geocoding Accuracy via Sensor Fusion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing mobile computer devices face inaccuracies and unavailability of GPS position information due to environmental obstructions and limitations in dense urban areas, requiring enhanced geocoding accuracy for precise location determination.
Innovation Solution
The use of on-board sensors such as accelerometers, gyroscopes, and compasses to determine net accelerations, velocities, and orientations, which are then processed to enhance the accuracy of GPS-derived positions by correlating sensor data with real-world geographic constraints and surface features, using machine learning algorithms to identify and map terrain elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If GPS satellites are used to determine position, then position information can be obtained globally, but accuracy deteriorates in dense urban environments with obstructions
Solution Approach 1:
The patent combines GPS position information with accelerometer data and surface feature information to create a fused location estimate. The system merges multiple data sources (GPS coordinates, acceleration patterns, terrain features) to compensate for GPS inaccuracies in urban environments, achieving more reliable and precise positioning than any single source alone.
Solution Approach 2:
The patent introduces surface features (terrain, landmarks, geographic constraints) as intermediary elements to bridge GPS coordinates and actual physical locations. By correlating accelerometer-derived position changes with known surface features, the system mediates between satellite position data and ground truth locations, improving accuracy in GPS-challenged environments.
2Ease of operation
If GPS position information is used alone, then location determination is simple, but accuracy deteriorates when signals are blocked or delayed by obstructions
Solution Approach 1:
The system merges GPS position data with accelerometer measurements and surface feature correlations to maintain location determination functionality while improving accuracy. The combination allows the system to operate simply when GPS is available and automatically incorporates additional processing when obstructions are detected.
Solution Approach 2:
The patent changes the parameter set used for position determination based on environmental conditions. When GPS signals are clear, the system uses only satellite coordinates. When obstructions are detected, the system transitions to using accelerometer integration and surface feature matching, changing the operational parameters dynamically to maintain both simplicity and accuracy.
3Reliability
If accelerometer data is integrated to determine position, then position can be estimated without GPS signals, but error accumulates over time
Solution Approach 1:
The patent implements feedback by continuously correlating accelerometer-derived position estimates with known surface features and geographic constraints. When the estimated position diverges from expected terrain features or when GPS signals become available, the system uses this feedback to correct accumulated errors and reset the integration baseline.
Solution Approach 2:
The system performs preliminary actions by pre-loading surface feature data and geographic constraints into the device. This preliminary preparation enables the accelerometer integration to be corrected against known terrain features without requiring real-time external references, reducing error accumulation during GPS-denied periods.
4Measurement precision
If multiple sensors are used to enhance geocoding accuracy, then position precision improves, but device complexity increases
Solution Approach 1:
The patent makes the sensor system multi-functional by using the accelerometer for multiple purposes: detecting surface features, determining position changes, and correcting GPS errors. This universal use of existing sensors enhances geocoding accuracy without requiring additional specialized hardware, thereby limiting the increase in device complexity.
Solution Approach 2:
The system uses the mobile device's existing sensors and onboard resources to enhance its own positioning capability. By utilizing the accelerometer, GPS receiver, and stored map data already present in the device, the system achieves improved geocoding accuracy through self-service rather than requiring external infrastructure or additional complex components.
Data Source
AI summary
Where a mobile computer device having a position sensor, such as a GPS sensor, and an accelerometer is configured to estimate a geographic position of the mobile computer device using the position sensor, the accuracy of such positions may be enhanced by correlating accelerations of the mobile computer device, as determined by the accelerometer, against the positions of known surface features within a vicinity of the estimated positions. If the observed accelerations are consistent with one of the known surface features, the location of the mobile computer device may be correlated with the location of the one of the known surface features.