Mobile Device State Tracking via Grid Probability Rebounding
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Solution Overview
Problem
Existing methods for tracking a mobile electronic device's state indoors or in urban areas face challenges due to limited and error-prone measurement sources, such as satellite-based systems, local wireless networks, and on-board sensors, which result in inaccurate position information and difficulties in combining diverse measurement sources with different error characteristics and nonlinearities.
Innovation Solution
A method using a grid representation of the state space with cells having probability values, where the grid is updated based on measurement signaling and rebounded to retain information from non-unique solutions, allowing for accurate propagation of the complete position distribution, including undetermined or multiple-solution systems, and utilizing a motion model for prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If satellite-based systems such as GPS are used for positioning, then position information can be obtained, but the systems become unpredictable and fail when used indoors in high-sensitivity mode
Solution Approach 1:
The patent combines multiple positioning systems (GPS, cellular networks, WLAN, Bluetooth) and on-board sensors (accelerometers, barometers, digital compasses) into a unified tracking system. This fusion allows the system to maintain reliability by switching between different measurement sources depending on the operating environment, while preserving measurement precision through selective use of appropriate sensors for indoor versus outdoor conditions.
2Reliability
If local wireless networks such as cellular network, WLAN or Bluetooth are used for positioning, then positioning capability is provided, but the accuracy is inferior when compared to GPS
Solution Approach 1:
The system merges local wireless network positioning with GPS and other sensor data. By combining these diverse measurement sources with different error characteristics, the system achieves both the availability of positioning capability (from cellular/WLAN/Bluetooth) and improved accuracy (through fusion with GPS and sensor data), resolving the contradiction between reliability and measurement precision.
3Loss of information
If the complete state space is represented with all possible cells, then all information is retained from measurement geometries, but the computation load increases significantly
Solution Approach 1:
The patent segments the state space into a grid of cells, where each cell represents a discrete region. This segmentation allows the system to retain information from measurement geometries by distributing probability values across multiple cells, while managing computation load through efficient grid-based operations and selective updating of only relevant cells based on measurement data.
Solution Approach 2:
The system performs partial action by updating only those grid cells that are relevant to the current measurement data, rather than processing the entire state space. This approach retains necessary information from measurement geometries while significantly reducing computation load by avoiding unnecessary calculations in regions with zero or negligible probability.
4Measurement precision
If commonly used Kalman filter and its nonlinear extensions are used, then filtering of measurement data is performed, but the systems can fail without warning when dealing with complex nonlinearities and missing data
Solution Approach 1:
The patent segments the continuous state space into discrete grid cells, transforming the complex nonlinear filtering problem into a more manageable discrete form. This segmentation allows the system to handle nonlinearities and missing data more robustly by distributing probability mass across multiple cells and using simple probabilistic updates rather than complex nonlinear transformations, thereby improving reliability while maintaining filtering capability.
Data Source
AI summary
The invention relates to a method of tracking a state of a mobile electronic device and to a mobile electronic device including processing apparatus arranged to perform the method.A method of tracking a state of a mobile electronic device, the method comprising iteratively performing:(i) representing the state of the mobile electronic device using a grid comprising a plurality of cells, each cell representing a region in state space defined by one or more state variables and having a probability value that the state of the mobile electronic device is within that region in state space, the grid being bounded to include only cells having a probability value above a predetermined threshold;(ii) obtaining measurement signalling indicating values of one or more state variables;(iii) updating the probability values of the grid based on the measurement signalling and rebounding the grid.