Positioning Method Using Virtual Anchor Adjustment
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Solution Overview
Problem
Existing positioning techniques, such as those using Extended Kalman filters, can diverge from true positions in complex environments, and require extensive calibration and are sensitive to configuration changes.
Innovation Solution
A computer-implemented method that estimates the position of a movable device by receiving observations from distributed anchors, estimating range and/or angle, adjusting anchor positions for device motion, and calculating the device's position within a defined time window.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If Extended Kalman filter is used for positioning, then positioning can be performed in dynamic environments, but the system diverges from true positions in complex environments and requires extensive calibration
Solution Approach 1:
The patent creates a virtual copy of the physical environment by constructing a signal propagation model that replicates how signals travel through the environment. This virtual model includes virtual anchors and virtual mobile devices that mirror the physical setup, allowing the system to simulate and predict signal behavior without requiring extensive real-world calibration. The virtual environment copy enables accurate positioning in complex environments by computing signal paths and strengths based on the modeled environment rather than relying on calibrated filter parameters.
Solution Approach 2:
The patent replaces the mechanical/mathematical filtering system (Extended Kalman filter) with a physics-based signal propagation model. Instead of using iterative mathematical estimation that requires calibration, the system uses electromagnetic wave propagation principles to directly compute position. This substitution eliminates the need for extensive calibration while maintaining reliability in complex environments, as the physics-based model naturally adapts to environmental characteristics without manual tuning.
2Measurement precision
If RF fingerprinting is used for positioning, then good positioning results can be achieved in ideal situations, but the lookup database construction is onerous and time-consuming
Solution Approach 1:
The patent performs preliminary modeling of the signal propagation environment to predict signal strengths and paths before actual positioning occurs. By pre-computing the virtual signal propagation model based on environmental geometry and material properties, the system eliminates the need for time-consuming on-site database collection. The preliminary action of creating the virtual model enables rapid positioning without the extensive surveying required by RF fingerprinting.
Solution Approach 2:
The patent creates a virtual copy of the signal propagation environment that can be queried for positioning without requiring a physical lookup database. Instead of collecting and storing actual signal measurements from every location in the environment, the system uses the virtual model to compute expected signal characteristics on-demand. This copying approach eliminates the time-consuming database construction while maintaining positioning accuracy.
3Measurement precision
If multiple sensors are combined for positioning, then location accuracy is improved, but the system complexity increases
Solution Approach 1:
The patent uses a virtual model to consolidate multiple sensor inputs into a unified positioning calculation. Instead of implementing complex sensor fusion algorithms that process data from multiple physical sensors separately, the virtual signal propagation model integrates all sensor information through a single coherent framework. The virtual environment computation naturally fuses geometric, signal strength, and temporal data without requiring separate processing pipelines, thereby reducing system complexity while maintaining the accuracy benefits of multi-sensor input.
Data Source
AI summary
A computer implemented method (600) for estimating the position of a movable device in an environment at a required time. First observations are taken (615) by first sensors at various times between the device and plural distributed anchors having known positions in the environment. For each observation taken at a time point within a time window (650), the range and/or angle from the device to the anchor is estimated (640), and the displacement of the device is estimated (660) between the time the observation was taken and the required time is estimated based on second observations taken (625) by second sensors. The position of the anchor is adjusted (665) by the displacement so as to compensate for the effect of the motion of the device. The position of the device (670,680) at the required time is calculated based on the ranges and/or angles and the adjusted anchor positions.