Accuracy in WiFi Access Point Position Estimation Using Round Trip Time.

Area of Science:

• Wireless positioning systems
• Indoor navigation technologies
• Geodetic surveying and geodesy

Background:

• WiFi Round Trip Time (RTT) offers meter-level positioning accuracy, surpassing Global Navigation Satellite Systems (GNSS) in indoor environments.
• Existing methods lack scalability and automation for WiFi Access Point (WAP) positioning and hardware bias estimation.
• WAP hardware biases significantly impact user terminal positioning accuracy.

Purpose of the Study:

• To develop a scalable and automated system for estimating WAP positions and hardware biases using WiFi RTT.
• To investigate the improvement in accuracy when incorporating raw GNSS measurements (pseudoranges, carrier phase) from user terminals.
• To enable accurate WAP product estimation for both mild-indoor and deep-indoor scenarios.

Main Methods:

• Proposed an 'inverse positioning' method to estimate WAP positions and hardware biases from terminal-provided ranges and position fixes.
• Evaluated the method's performance using a benign, open-sky scenario to establish an upper bound on positioning error.
• Assessed the integration of raw GNSS measurements to enhance the accuracy of WAP product estimation.

Main Results:

• Achieved WAP position and hardware bias accuracies better than 1.5 meters under benign conditions.
• Demonstrated the method's suitability for automated implementation, eliminating the need for dedicated WAP surveying campaigns.
• Successfully estimated WAP products for both mild-indoor (WiFi RTT + GNSS) and deep-indoor (WiFi RTT only) environments.

Conclusions:

• The proposed inverse positioning method provides an automated and accurate solution for WAP positioning and bias estimation.
• The technique enhances indoor navigation capabilities by leveraging WiFi RTT measurements.
• This approach facilitates the deployment of accurate positioning services in diverse indoor environments without manual WAP calibration.