Enhanced Location Trilateration via Kalman Filter Waypoint Ranking
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Solution Overview
Problem
Current mobile devices lack the ability to provide accurate and reliable three-dimensional location information, especially in indoor or urban environments where satellite signals are obstructed, leading to inconsistent and inaccurate location-based services.
Innovation Solution
A method that involves receiving location information from multiple external devices, normalizing and ranking waypoints, and applying them to a Kalman filter to generate a final location waypoint, which includes selecting four suitable waypoints from memory based on overall and device-specific rankings to enhance location determination accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional GPS satellite signals are used for location determination, then location services can be provided in open environments, but location accuracy deteriorates significantly in indoor or urban environments where satellite signals are obstructed
Solution Approach 1:
The patent combines multiple location determination approaches (GPS satellite signals, Wi-Fi positioning, cellular tower triangulation, and inertial sensors) into a unified location service system. This fusion of multiple positioning methods ensures reliable location services in both open and obstructed environments by compensating for the weaknesses of individual methods with the strengths of others.
Solution Approach 2:
The system dynamically changes operational parameters based on environment detection. When satellite signals are obstructed (detected through signal strength and availability metrics), the system transitions to alternative positioning methods using Wi-Fi access points, cellular towers, or inertial measurement units, thereby maintaining location accuracy across different environmental conditions.
2Measurement precision
If multiple location determination methods are combined to improve accuracy in obstructed environments, then location precision improves, but system complexity increases
Solution Approach 1:
The mobile device is designed with multi-functional capabilities, integrating GPS receiver, Wi-Fi positioning module, cellular communication interface, and inertial sensors into a single universal location determination system. This multi-functionality allows the device to perform various positioning methods without requiring separate dedicated systems, thereby managing complexity while maintaining accuracy.
Solution Approach 2:
The system employs dynamic selection and weighting of different location determination methods based on current environmental conditions and signal availability. The processor continuously evaluates the reliability of each positioning source and adjusts their contribution to the final location calculation, optimizing accuracy while minimizing the activation of unnecessary system components.
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 provides more precise and reliable three-dimensional location information, suitable for emergency, commercial, and internal location services, improving the accuracy and consistency of location-based services in challenging environments.
Implementation Method 1
applying the four selected waypoints to a kalman filter to generate a final location waypoint
Data Source
AI summary
Method, systems and devices for determining for performing enhanced location based trilateration include receiving location information (e.g., waypoints) from one or more external devices, determining the validity of the received location information, performing normalization operations to normalize the received location information, assigning an overall ranking and a device-specific ranking to the location information, and storing the validated and normalized location information in memory. The enhanced location based trilateration may also include selecting four locations (e.g., waypoints) from the memory based on a combination of the overall ranking and the device-specific ranking, and generating a final location value or waypoint based on a result of applying the four selected waypoints to a kalman filter. The output of the kalman filter may also be reported and/or used as the device's current location.