Indoor Location Estimation Using Wi-Fi Signal Multilateration
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Solution Overview
Problem
Existing indoor location tracking methods, particularly in multi-story buildings, face challenges in accurately pinpointing the location of electronic devices due to the unreliability of GPS signals and errors in methods like free space path loss equations and non-linear least squares methods.
Innovation Solution
A method that uses a transceiver to detect multiple Wi-Fi signals, process signal strength indicators, and apply a multilateration function with varying constants to minimize error in distance calculations, leveraging a free space path loss equation and error calculation functions like mean square error to estimate the location of electronic devices within buildings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS signals are used to determine device location, then outdoor location can be obtained, but indoor location precision deteriorates
Solution Approach 1:
The patent introduces Wi-Fi access points as intermediary objects to enable location determination indoors. Instead of relying directly on GPS satellites which are blocked by buildings, the system uses locally available Wi-Fi signals from access points within the building as mediators to calculate device position through multilateration algorithms.
Solution Approach 2:
The patent replaces the GPS satellite-based electromagnetic positioning system with a local Wi-Fi network-based positioning system. The free space path loss equation substitutes the GPS distance calculation method, using signal strength measurements from Wi-Fi access points instead of satellite signals to determine device location.
2Measurement precision
If free space path loss equation is used for distance calculation, then location estimation can be performed, but measurement precision deteriorates due to constant selection errors
Solution Approach 1:
The patent transforms the constant K from a static, pre-determined value to a dynamic parameter that is optimized during the location calculation process. By treating K as a variable to be solved for through the multilateration function, the system adapts the constant to the specific indoor environment and signal conditions, improving distance calculation accuracy.
Solution Approach 2:
The patent changes the approach to the constant K by incorporating it as an optimization variable in the multilateration function. Instead of using a fixed value or simple empirical selection, the system varies K to minimize the multilateration error, effectively changing how this critical parameter is determined to improve overall measurement precision.
3Measurement precision
If multiple candidate constants are tested to minimize error, then location accuracy improves, but computational complexity increases
Solution Approach 1:
The patent defines a clear objective function (multilateration error) before performing the optimization, which guides the selection of candidate constants and the evaluation process. By establishing the error minimization criterion in advance, the system can efficiently evaluate multiple constants and select the optimal one without exhaustive search, reducing computational complexity while maintaining accuracy.
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
This approach enables precise location estimation of electronic devices indoors without additional hardware, reducing errors and improving accuracy by optimizing constants in the free space path loss equation, thus enhancing the reliability of indoor location tracking.
Implementation Method 1
The second calculation to determine the second distances may include a free space path loss equation. The free space loss equation may: Log(d)=(K−20 Log(f)−RSSI)/20 in which K is the constant; f is the frequency of the detected signal; and RSSI is the signal strength indicator
Data Source
AI summary
A method of estimating indoor location of an electronic device is disclosed. The electronic device will detect multiple Wi-Fi signals, each of which originates from a unique Wi-Fi access point in a building. For each of the signals, the system will determine an access point device identifier and a signal strength indicator, retrieve location coordinates for the access point; and various candidate constants to apply to a distance calculation for determining a distance from the electronic device to each of the access points. The system will repeat the distance calculation multiple times for each of the various constants and determine which constant minimizes a loss value. The system will identify a set of coordinates of the electronic device that are associated with the constant that minimizes the loss value, and then use the coordinates to estimate a location of the electronic device within the building.