Indoor Localization Using Wi-Fi Signal Variance
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Solution Overview
Problem
Existing indoor localization technologies face challenges in accurately determining the floor of a multi-story building due to signal attenuation and dispersion, requiring a cost-effective and technically simpler method for inter-floor location determination in indoor environments.
Innovation Solution
A method and apparatus using Wi-Fi signals to measure and predict reception signal strengths, calculating variance values to estimate the current location by considering inter-floor signal loss, with an equation (RSSIP=RSSIi−Lf*|FloorIDi−P|) to select the correct floor.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS is used for indoor localization, then outdoor localization performance is optimal, but signal attenuation and dispersion occur in indoor environments
Solution Approach 1:
The patent uses Wi-Fi signals as an intermediary to achieve indoor localization. Instead of directly using GPS signals that attenuate indoors, the system employs Wi-Fi access points as mediators to transmit localization data through the indoor environment, resolving the contradiction between GPS outdoor optimality and indoor signal reliability
Solution Approach 2:
The patent replaces the GPS-based outdoor localization system with a Wi-Fi-based indoor localization system. This substitution involves replacing the fundamental localization mechanism from satellite-based radio waves to wireless network-based signals, enabling the system to function reliably in indoor environments where GPS fails
2Adaptability or versatility
If AOA and TOA techniques are used for wireless localization, then localization functionality is achieved, but additional devices are required for angle measurement and time synchronization
Solution Approach 1:
The patent adopts RSS (Received Signal Strength) measurement as a simpler, lower-cost alternative to AOA and TOA techniques. Instead of requiring complex angle measurement devices or time synchronization hardware, the system uses readily available signal strength measurements from Wi-Fi access points, reducing device complexity while maintaining localization functionality
Solution Approach 2:
The patent changes the measurement parameter from angle-based (AOA) or time-based (TOA) parameters to signal strength-based (RSS) parameters. This parameter change simplifies the required hardware by eliminating the need for angle sensors and time synchronization devices, as signal strength can be measured with standard wireless network components
3Ease of manufacture
If RSS technique is used for localization, then implementing cost is reduced, but localization accuracy in multi-story buildings is compromised
Solution Approach 1:
The patent extends the traditional two-dimensional horizontal localization to three-dimensional spatial localization by incorporating vertical floor information. By adding the floor dimension and using multiple access points across different floors, the system achieves accurate three-dimensional positioning while maintaining the low cost of RSS measurements
Solution Approach 2:
The patent performs preliminary actions by pre-establishing a database of access point locations and signal characteristics across multiple floors before actual localization occurs. This pre-processing enables the system to accurately determine floor information and calculate three-dimensional positions without requiring complex real-time measurements, maintaining both low cost and high accuracy
Data Source
AI summary
Disclosed is a method for determining an indoor location which includes receiving signals including IDs and information on floors from a plurality of APs that is provided at floors of the multi-story building; measuring reception signal strengths of the received signals, and selecting candidate floors by using the measured reception signal strengths; predicting reception signal strengths of the other candidate floors by using the reception signal strengths of the APs provided at the respective candidate floors; and calculating variance values for the reception signal strengths of the candidate floors, and estimating a current location by using the variance values.