Invisible Access Point Probability Estimation for Indoor Positioning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional Wi-Fi positioning systems indoors face limitations due to reliance on visible Access Points (APs), which represent only a small percentage of available APs, leading to reduced positioning accuracy due to the exclusion of invisible APs that carry useful information.
Innovation Solution
Incorporating invisible APs into the positioning system by dynamically estimating their probability and integrating their signal information with visible APs using a scanning module, distance calculator, and position estimator to enhance location determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system relies only on visible APs for positioning, then the system complexity is reduced and operation is simpler, but the positioning accuracy deteriorates because invisible APs carrying useful information are excluded
Solution Approach 1:
The system performs preliminary actions by collecting signal strength information from all APs in the database before actual positioning occurs. It pre-calculates distances and identifies both visible and invisible APs, so that when positioning is needed, the calculations are already prepared or can be quickly completed with minimal additional processing
Solution Approach 2:
The system dynamically adapts by adjusting the set of APs used for positioning based on real-time conditions. It flexibly incorporates both visible APs (detected by scanner) and invisible APs (inferred from database) depending on their availability and reliability, optimizing the positioning solution for each specific situation rather than using a fixed approach
2Measurement precision
If the system incorporates both visible and invisible APs, then the positioning accuracy is improved, but the computational complexity and processing time increase
Solution Approach 1:
Distance calculations and AP identification are performed in advance or during idle periods, so that when positioning is required, the system can quickly retrieve pre-computed results or complete calculations with minimal additional time
Solution Approach 2:
The system uses the database of AP locations and signal characteristics to self-determine which APs are invisible and should be incorporated, reducing the need for complex real-time analysis or external assistance in identifying the optimal set of APs for positioning
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Improves positioning accuracy by leveraging the information from both visible and invisible APs, providing a more precise geodetic location estimation compared to systems relying solely on visible APs.
Implementation Method 1
User device 102 communicates with AP 106-112 via a Wi-Fi communication channel 114
Implementation Method 2
The propagation model for Wi-Fi communication channel 114 is usually approximated by the log normal shadowing model
Data Source
AI summary
A method for incorporating invisible APs for RSSI based indoor positioning is presented. An empirical estimate of the probability of invisible APs versus distance is computed. An estimated position of the receiver can be computed using any statistical estimator based on the probability. In one embodiment, an estimate of the probability is computed by combining the probability over a set of visible APs and the probability over a set of invisible APs with the probability of individual contribution. In one embodiment a dynamic procedure is used to update the invisible probability that is computed using an AP dictionary built on the fly as new APs are detected. Incorporating invisible APs for estimating user position from the RSSI measurements for indoor positioning provides a better positioning accuracy as compared to typical estimators which rely only on the visible APs.