Ground Imaging Sensor for Vehicle Location Estimation
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Solution Overview
Problem
Existing location systems for moving vehicles, such as GPS and inertial navigation, face limitations in precision, accuracy, and susceptibility to interference, requiring improved methods for reliable and precise self-location and motion determination.
Innovation Solution
The use of a ground imaging sensor, like a camera, to analyze the ground surface and compare extracted features with a map database to estimate location and motion, leveraging image analysis and geo-location associations for accurate vehicle positioning and motion tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If GPS receivers are used for location estimation, then location information can be obtained, but precision and accuracy are limited and the system is susceptible to jamming and denial of service
Solution Approach 1:
The patent introduces ground imaging sensors and map databases as intermediary elements between the vehicle and the location determination process. Instead of directly relying on satellite signals, the system captures images of ground features, extracts features from these images, and compares them against pre-stored map databases to indirectly determine location, thereby avoiding direct susceptibility to GPS jamming while achieving precise location estimation
Solution Approach 2:
The patent replaces the electromagnetic signal-based GPS system with an optical imaging-based location determination system. By substituting the mechanical/optical approach (imaging sensors capturing ground features) for the electromagnetic approach (GPS satellite signals), the system achieves immunity to radio frequency jamming while maintaining or improving location precision through feature-based matching
2Measurement precision
If additional technology and equipment are used to overcome GPS limitations, then location accuracy may be improved, but the system becomes expensive
Solution Approach 1:
The patent makes the imaging sensor serve multiple functions: it captures images for location determination, extracts features for motion estimation, and provides data for both positioning and navigation tasks. This multi-functionality eliminates the need for separate specialized equipment for each function, reducing overall system complexity and cost while maintaining high location accuracy
Solution Approach 2:
The system uses the vehicle's existing imaging infrastructure (cameras already present for other purposes) to perform location determination. By making the imaging sensor serve itself for multiple purposes including location estimation, the system avoids additional expensive specialized equipment while achieving improved location accuracy through clever algorithmic processing of existing sensor data
3Ease of operation
If inertial navigation systems are used for self location, then location can be determined from a known starting point, but the systems require calibration and drift over time requiring periodic re-calibration
Solution Approach 1:
The patent implements a feedback mechanism where the imaging sensor continuously captures ground features and compares them against the map database to provide ongoing location verification. This feedback loop prevents drift accumulation by periodically correcting the position estimate based on visual landmark matching, eliminating the need for manual recalibration while maintaining high location reliability over extended periods
Data Source
AI summary
A system and method for estimating location and motion of an object. An image of a ground surface is obtained and a first set of features is extracted from the image. A map database is searched for a second set of features that match the first set of features and a geo-location is retrieved from the map database, wherein the geo-location is associated with the second set of features. The location is estimated based on the retrieved geo-location. The motion of the object, such as distance travelled, path travelled and/or speed may be estimated in a similar manner by comparing the location of extracted features that are present in two or more images over a selected time period.