Signal Strength Distribution Map Using Radial Basis Functions
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Solution Overview
Problem
Existing wireless positioning systems face challenges in accurately establishing signal strength distribution maps in indoor environments due to complex furnishings and non-line of sight signal propagation, leading to errors in position estimation, particularly with TOA and AOA techniques, and insufficient representation of actual signal strength distributions using linear interpolation with limited measuring locations.
Innovation Solution
A method and system that utilize a wireless positioning system with multiple base stations and a coordinating device to establish distribution functions based on measured signal strengths, adjusting these functions using radial basis functions or thin plate spline models, and computing estimated signal strengths at non-measuring locations to create a more accurate signal strength distribution map.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If linear interpolation is used to compute signal strength values at non-measuring locations, then computation complexity is low, but the signal strength distribution map does not sufficiently represent the actual signal strength distribution
Solution Approach 1:
The patent transforms the signal strength distribution estimation problem from simple linear interpolation to a parameter-based modeling approach using radial basis functions. By changing the mathematical model parameters from linear to radial basis functions with adjustable centers and widths, the system achieves higher accuracy while maintaining reasonable computational complexity through parameter optimization rather than exhaustive calculation.
Solution Approach 2:
The patent introduces radial basis functions as an intermediary mathematical model between the measured signal strength data and the estimated distribution map. These functions act as mediators that smoothly interpolate between measuring locations while capturing the underlying signal propagation patterns, thereby improving representation accuracy without requiring direct measurement at every location.
2Measurement precision
If more measuring locations are deployed to measure signal strengths, then the signal strength distribution map accuracy is improved, but the amount of measuring locations is limited in practice
Solution Approach 1:
The patent performs preliminary action by establishing a radial basis function model structure before actual signal strength measurements are taken. The model framework, including the selection of basis function centers and initial parameter settings, is prepared in advance, allowing subsequent measurements to be efficiently processed and integrated into the distribution map without requiring extensive on-site measurement activities.
Solution Approach 2:
The patent creates a mathematical copy of the signal strength distribution through radial basis functions that replicates the underlying propagation patterns. Instead of physically measuring at every possible location, the system creates a computational model that copies and extrapolates the signal distribution characteristics from limited measurement points across the entire area.
3Measurement precision
If TOA-based or AOA-based techniques are used for position estimation, then distance or direction can be calculated, but the multipath effect in indoor environments causes significant errors
Solution Approach 1:
The patent converts the harmful multipath effect into a beneficial modeling opportunity by using radial basis functions that can adapt to the actual signal propagation environment. Instead of treating multipath reflections as noise to be eliminated, the system uses the measured signal strengths (which already contain multipath effects) to train and adjust the radial basis function model, thereby capturing the real-world propagation characteristics including reflections and diffractions.
Data Source
AI summary
A signal strength distribution establishing method includes establishing a plurality of distribution functions corresponding to a plurality of base stations; measuring a plurality of signal strengths from the plurality of base stations on at least a measuring location in an area to obtain a plurality of signal strengths measured values; adjusting the plurality of distribution functions according to the plurality of signal strengths on the at least a measuring location; computing a plurality of signal strength estimated values corresponding to a plurality of locations within the area according to the plurality of adjusted distribution functions; and establishing a signal strength distribution map corresponding to the area according to the plurality of signal strength measured values and the plurality of signal strength estimated values.