Radio Field Intensity State Estimation for Position Accuracy
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Solution Overview
Problem
Existing position estimation techniques based on radio field intensity have low accuracy due to noise superimposed on observed values, leading to stochastic variations and inaccuracies in calculated positions.
Innovation Solution
A position estimation apparatus and method that acquire time-series data from known and unknown observation points, estimate radio field intensity states, and compare these states to estimate the position of the unknown point, reducing noise effects through a two-step state estimation process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If position estimation is performed based on observed radio field intensity values, then position information can be obtained, but noise superimposed on observation values causes stochastic variations and reduces estimation accuracy
Solution Approach 1:
The patent applies preliminary action by performing state estimation on radio field intensity values before using them for position estimation. The state estimation unit estimates the true state of radio field intensity from observed values, removing noise effects in advance. This preliminary processing step ensures that the position estimation unit receives clean, reliable data, thereby improving position estimation accuracy while maintaining estimation stability.
2Measurement precision
If direct position estimation is performed from observed radio field intensity values, then the process is simple, but noise causes inaccurate position calculation
Solution Approach 1:
The patent applies segmentation by dividing the position estimation process into two distinct functional units: a state estimation unit and a position estimation unit. The state estimation unit first estimates the true radio field intensity state from noisy observations, and then the position estimation unit uses these cleaned values for position calculation. This segmentation isolates the noise filtering function from the position estimation function, improving accuracy while keeping each unit's complexity manageable.
Data Source
AI summary
An estimation unit 32 estimates, from each of acquired first time-series data pieces, a state of a radio field intensity at a position of an apparatus 10 that corresponds to each of the first time-series data pieces. The estimation unit 32 estimates, from second time-series data, a state of the radio field intensity at a position of an apparatus 20. An estimation unit 33 estimates a state of the radio field intensity at each point in a target space by using the position of each apparatus 10 and the state of the radio field intensity thereof. An estimation unit 34 compares the state at each point with the state at the position of the apparatus 20 and thereby estimates the position of the apparatus 20. An estimation unit 35 estimates a position state of the apparatus 20 based on time-series data of the position of the apparatus 20.