PDR Algorithm Step Size Adjustment for Indoor Positioning
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Solution Overview
Problem
Traditional indoor positioning systems using back-end positioning engines suffer from data lags, leading to positioning deviations, especially in complex navigation paths due to Pedestrian Dead Reckoning (PDR) data delays.
Innovation Solution
An indoor positioning method that adaptively adjusts the step size of the PDR positioning algorithm based on the distance between the positioning terminal and virtual beacons, decreasing the step size when the distance decreases and increasing it when the distance increases, to improve positioning accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the step size of the PDR positioning algorithm is kept large for efficiency, then positioning speed is improved, but positioning accuracy deteriorates due to data lags in complex navigation paths
Solution Approach 1:
The patent applies dynamics by making the step size of the PDR positioning algorithm variable rather than fixed. The step size dynamically adjusts based on the terminal's movement state: when acceleration exceeds a threshold (indicating turning or stopping), the step size decreases to improve accuracy; when movement is steady, the step size increases to maintain speed. This dynamic adjustment resolves the contradiction between positioning speed and accuracy.
Solution Approach 2:
The patent changes the parameter of step size based on detected movement conditions. By monitoring acceleration data and comparing it against thresholds, the system modifies the step size parameter adaptively - reducing it during turns or stops where accuracy is critical, and maintaining or increasing it during straight-line movement where speed is prioritized. This parameter change strategy directly addresses the speed-accuracy tradeoff.
2Device complexity
If the positioning algorithm uses fixed step size for simplicity, then device complexity is reduced, but positioning accuracy deteriorates in complex navigation scenarios
Solution Approach 1:
The positioning algorithm performs self-service by automatically detecting its own operational state through acceleration monitoring and autonomously adjusting its step size parameter. The system uses its built-in sensors and processing capabilities to identify when it needs higher accuracy (during turns or stops) and adjusts accordingly without external intervention. This self-adjusting mechanism maintains simplicity while improving accuracy in complex navigation scenarios.
Data Source
AI summary
An indoor positioning method includes judging whether a positioning terminal enters a coverage range of a virtual beacon. If yes, judging whether a distance between the positioning terminal and the virtual beacon gradually decreases to obtain a judgement result, according to the judgement result, adjusting the step size of a PDR positioning algorithm. When the distance gradually decreases, the step size of the PDR positioning algorithm is decreased, and when the distance gradually increases, the step size of the PDR positioning algorithm is increased. The positioning terminal is then positioned by a PDR positioning algorithm with the step size adjusted to obtain a positioning result. If not, the positioning terminal is positioned by a PDR positioning algorithm with the step size not adjusted to obtain a positioning result. According to the present invention positioning can be more accurate by adaptively adjusting the step size in the PDR positioning algorithm.