Sensor-Based Geolocation Using Optimization Algorithms
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Solution Overview
Problem
GPS information is often unavailable or insufficiently accurate in indoor, underground, or areas without unobscured access, leading to poor location accuracy using dead reckoning techniques due to compounded errors over time and distance.
Innovation Solution
A user device utilizes sensor measurements and optimization processes, such as hill climber algorithms or particle swarm optimization, to determine location with reduced error rates, even when GPS is unavailable, and stores this information for subsequent geolocation without dead reckoning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If dead reckoning techniques are used to determine location without GPS, then location determination is possible in indoor or GPS-denied environments, but location accuracy deteriorates due to compounded errors over time and distance
Solution Approach 1:
The system collects sensor measurements (accelerometer, gyroscope, magnetometer, barometer) continuously and uses optimization algorithms to compare predicted positions with actual sensor data, providing feedback to correct accumulated errors in dead reckoning calculations
Solution Approach 2:
The system changes the parameters used for location determination by incorporating multiple sensor modalities and using optimization algorithms (hill climber, particle swarm optimization) to find the most likely position based on sensor measurement patterns rather than relying solely on integrated accelerometer/gyroscope data
2Measurement precision
If sensor measurements and optimization processes are used to improve location accuracy, then location precision improves in GPS-denied environments, but computational complexity and processing time increase
Solution Approach 1:
The system applies multiple optimization algorithms (hill climber, particle swarm optimization) and processes data from multiple sensors simultaneously, using more computational resources than a single algorithm would require to achieve higher location accuracy
Solution Approach 2:
The system segments the location determination problem into multiple independent sensor measurements (acceleration, orientation, magnetic field, pressure) that are processed separately and then combined through optimization algorithms to determine the final position
Data Source
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AI summary
A device may determine a set of orientations or relative displacements at a set of locations. The set of locations may include at least a first location and a second location. The device may determine a set of sensor measurements relating to one or more measurable parameters at the set of locations. The device may determine, based on the set of orientations or relative displacements at the set of locations and the set of sensor measurements relating to the one or more measurable parameters at the set of locations, a path relating to the set of locations. The device may perform an action based on determining the path.