Sensor Frame Mapping for Geolocation in GPS-Denied Environments
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Solution Overview
Problem
Existing methods for obtaining geospatial coordinates from sensor data, such as GPS, are inaccurate or unavailable in environments like tunnels, and fail to account for sensor operations like zooming or rotation.
Innovation Solution
A method that analyzes successive frames of sensor data to determine transformations like translation, rotation, and zooming, and maps these transformations to GPS coordinate changes, allowing accurate GPS coordinate estimation even when GPS data is missing or unreliable.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If GPS sensor is used to obtain geospatial coordinates, then geospatial coordinates can be obtained in open environments, but GPS signals are unavailable or unreliable in tunnels causing loss of geospatial coordinates
Solution Approach 1:
The patent uses visual features from sensor data frames as an intermediary to establish correspondence between GPS coordinates and sensor data when GPS is available, then uses this correspondence to estimate coordinates when GPS is unavailable. The visual features act as a mediator that links the GPS coordinate system to the sensor data coordinate system, enabling coordinate estimation without direct GPS signals.
Solution Approach 2:
The patent performs preliminary actions by establishing the mapping relationship between GPS coordinates and sensor data coordinates in advance when GPS signals are available. It pre-processes the sensor data to identify corresponding elements and creates a transformation model that can be applied later when GPS is unavailable, rather than waiting for the GPS-denied environment to occur.
2Loss of information
If current techniques estimate geospatial coordinates using previous and/or subsequent frames, then geospatial coordinates can be obtained in GPS-denied environments, but the estimation is inaccurate
Solution Approach 1:
The patent uses feedback by continuously refining the mapping relationship between sensor coordinates and GPS coordinates using frames where GPS is available. It adjusts the transformation parameters based on the correspondence between visual features and GPS coordinates, creating a feedback loop that improves the accuracy of coordinate estimation in GPS-denied environments through iterative refinement.
Solution Approach 2:
The patent replaces the mechanical GPS signal reception system with a visual-based coordinate estimation system. Instead of relying on electromagnetic GPS signals that fail in tunnels, it substitutes a computer vision-based approach that uses image feature correspondence and geometric transformations to estimate coordinates, effectively replacing one physical system with another that works in the given environment.
3Device complexity
If sensor operations like zooming or rotation are not accounted for, then processing is simpler, but geospatial coordinate accuracy deteriorates
Solution Approach 1:
The patent applies dynamics by making the coordinate transformation system adaptive to changing sensor conditions. It dynamically adjusts the transformation model to account for zooming, rotation, and other sensor operations by detecting changes in the sensor data and updating the mapping parameters accordingly, rather than using a static transformation that assumes fixed sensor orientation and magnification.
Data Source
AI summary
Systems and methods are provided for one or more processors; and memory storing instructions that, when executed by the one or more processors, cause the system to perform: receiving successive frames of sensor data, the successive frames comprising a first frame and a second frame; determining transformations, in sensor coordinates, between coordinates of corresponding elements in the successive frames; determining a mapping between the transformations in sensor coordinates and transformations in geospatial coordinates of the corresponding elements in the successive frames; and determining second geospatial coordinates of the corresponding elements of a third frame based on: a transformation between the second frame and the third frame, and the mapping.