Accuracy in WiFi Access Point Position Estimation Using Round Trip Time
WiFi Round Trip Time (RTT) unlocks meter level accuracies in user terminal positions where no other navigation systems, such as Global Navigation Satellite Systems (GNSS), are able to (e.g., indoors). However, little has been done so far to obtain a scalable and automated system that computes the po...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-06-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/11/3828 |
| _version_ | 1827690916496801792 |
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| author | Miquel Garcia-Fernandez Isaac Hoyas-Ester Alex Lopez-Cruces Malgorzata Siutkowska Xavier Banqué-Casanovas |
| author_facet | Miquel Garcia-Fernandez Isaac Hoyas-Ester Alex Lopez-Cruces Malgorzata Siutkowska Xavier Banqué-Casanovas |
| author_sort | Miquel Garcia-Fernandez |
| collection | DOAJ |
| description | WiFi Round Trip Time (RTT) unlocks meter level accuracies in user terminal positions where no other navigation systems, such as Global Navigation Satellite Systems (GNSS), are able to (e.g., indoors). However, little has been done so far to obtain a scalable and automated system that computes the position of the WiFi Access Points (WAP) using RTT and that is able to estimate, in addition to the position, the hardware biases that offset the WiFi ranging measurements. These biases have a direct impact on the ultimate position accuracy of the terminals. This work proposes a method in which the computation of the WiFi Access Points positions and hardware biases (i.e., products) can be estimated based on the ranges and position fixes provided by user terminals (i.e., <i>inverse positioning</i>) and details how this can be improved if raw GNSS measurements (pseudoranges and carrier phase) are also available in the terminal. The data setup used to obtain a performance assessment was configured in a benign scenario (open sky with no obstructions) in order to obtain an upper boundary on the positioning error that can be achieved with the proposed method. Under these conditions, accuracies better than 1.5 m were achieved for the WAP position and hardware bias. The proposed method is suitable to be implemented in an automated manner, without having to rely on dedicated campaigns to survey 802.11mc-compliant WAPs. This paper offers a technique to automatically estimate both mild-indoor WAP products (where terminals have both Wi-Fi RTT and GNSS coverage) and deep-indoor WAP (with no GNSS coverage where the terminals obtain their position exclusively from previously estimated mild-indoor WAPs). |
| first_indexed | 2024-03-10T10:48:44Z |
| format | Article |
| id | doaj.art-5548aea0fda8487f91991245fe26f87f |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T10:48:44Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-5548aea0fda8487f91991245fe26f87f2023-11-21T22:22:16ZengMDPI AGSensors1424-82202021-06-012111382810.3390/s21113828Accuracy in WiFi Access Point Position Estimation Using Round Trip TimeMiquel Garcia-Fernandez0Isaac Hoyas-Ester1Alex Lopez-Cruces2Malgorzata Siutkowska3Xavier Banqué-Casanovas4Rokubun S.L., 08018 Barcelona, SpainRokubun S.L., 08018 Barcelona, SpainRokubun S.L., 08018 Barcelona, SpainRokubun S.L., 08018 Barcelona, SpainRokubun S.L., 08018 Barcelona, SpainWiFi Round Trip Time (RTT) unlocks meter level accuracies in user terminal positions where no other navigation systems, such as Global Navigation Satellite Systems (GNSS), are able to (e.g., indoors). However, little has been done so far to obtain a scalable and automated system that computes the position of the WiFi Access Points (WAP) using RTT and that is able to estimate, in addition to the position, the hardware biases that offset the WiFi ranging measurements. These biases have a direct impact on the ultimate position accuracy of the terminals. This work proposes a method in which the computation of the WiFi Access Points positions and hardware biases (i.e., products) can be estimated based on the ranges and position fixes provided by user terminals (i.e., <i>inverse positioning</i>) and details how this can be improved if raw GNSS measurements (pseudoranges and carrier phase) are also available in the terminal. The data setup used to obtain a performance assessment was configured in a benign scenario (open sky with no obstructions) in order to obtain an upper boundary on the positioning error that can be achieved with the proposed method. Under these conditions, accuracies better than 1.5 m were achieved for the WAP position and hardware bias. The proposed method is suitable to be implemented in an automated manner, without having to rely on dedicated campaigns to survey 802.11mc-compliant WAPs. This paper offers a technique to automatically estimate both mild-indoor WAP products (where terminals have both Wi-Fi RTT and GNSS coverage) and deep-indoor WAP (with no GNSS coverage where the terminals obtain their position exclusively from previously estimated mild-indoor WAPs).https://www.mdpi.com/1424-8220/21/11/3828WiFiRound Trip Timefine time measurementsAccess PointsGNSSnavigation |
| spellingShingle | Miquel Garcia-Fernandez Isaac Hoyas-Ester Alex Lopez-Cruces Malgorzata Siutkowska Xavier Banqué-Casanovas Accuracy in WiFi Access Point Position Estimation Using Round Trip Time Sensors WiFi Round Trip Time fine time measurements Access Points GNSS navigation |
| title | Accuracy in WiFi Access Point Position Estimation Using Round Trip Time |
| title_full | Accuracy in WiFi Access Point Position Estimation Using Round Trip Time |
| title_fullStr | Accuracy in WiFi Access Point Position Estimation Using Round Trip Time |
| title_full_unstemmed | Accuracy in WiFi Access Point Position Estimation Using Round Trip Time |
| title_short | Accuracy in WiFi Access Point Position Estimation Using Round Trip Time |
| title_sort | accuracy in wifi access point position estimation using round trip time |
| topic | WiFi Round Trip Time fine time measurements Access Points GNSS navigation |
| url | https://www.mdpi.com/1424-8220/21/11/3828 |
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