Abstract
More and more applications of location-based services lead to the development of indoor positioning technology. Wi-Fi-based indoor localization has been attractive due to its extensive distribution and low cost properties. IEEE 802.11-2016 now includes a Wi-Fi Fine Time Measurement (FTM) protocol which provides a more robust approach for Wi-Fi ranging between the mobile terminal and Wi-Fi access point (AP). To improve the positioning accuracy, in this paper, we propose a robust dead reckoning algorithm combining the results of Wi-Fi FTM and multiple sensors (DRWMs). A real-time Wi-Fi ranging model is built which can effectively reduce the Wi-Fi ranging errors, and then a multisensor multi-pattern-based dead reckoning is presented. In addition, the Unscented Kalman filter (UKF) is applied to fuse the results of Wi-Fi ranging model and multiple sensors. The experiment results show that the proposed DRWMs algorithm can achieve accurate localization performance in line-of-sight/non-line-of-sight (LOS)/(NLOS) mixed indoor environment. Compared with the traditional Wi-Fi positioning method and the traditional dead reckoning method, the proposed algorithm is more stable and has better real-time performance for indoor positioning.
Highlights
In Global Navigation Satellite System (GNSS)-denied indoor environments, various indoor localization systems based on different techniques, such as ultra- wideband (UWB) [1], bluetooth [2], Wi-Fi [3], light source [4], and multi-sensors [5] have been developed for location-based services (LBS)
T−nhoe(tx...epjd2o−tshixtai1ot2n)th−oef(nyWuj2mi−-Fbyie1Ar2)oPf, AanPds where xp is the localization result, j is the number of access point (AP), xj and yj are the position of Wi-Fi AP, and DRTT(j) is real-time round-trip time (RTT) data received from each Wi-Fi AP
Where Li is the measured distance, i is used to differentiate different APs, L0 is the extra ranging distance caused by multipath, P = [x0 y0]T indicates the location of mobile terminal, Pi is the location of Wi-Fi AP, P −Pi is the matrix norm that indicates the Euclidean distance between mobile terminal and Wi-Fi AP, ei is the NLOS error which indicates the difference between the final propagation distance of the signal and the true straight line distance when LOS path is lacked [45], drandom is the random error of measurements which confront to a zero-mean Gaussian distribution with a variance of 0.25 [14], and ∆trandom is defined in Equation (10)
Summary
In Global Navigation Satellite System (GNSS)-denied indoor environments, various indoor localization systems based on different techniques, such as ultra- wideband (UWB) [1], bluetooth [2], Wi-Fi [3], light source [4], and multi-sensors [5] have been developed for location-based services (LBS). When giving a complex indoor scenario where the direct transmission path between the transceivers is blocked, the distance errors measured by Wi-Fi FTM cannot be eliminated due to the lack of a line-of-sight (LOS) path [15]. This paper proposes a robust dead reckoning algorithm based on Wi-Fi FTM and multiple sensors (DRWMs). (3) Based on the fusion of Wi-Fi ranging model and multi-pattern-based dead reckoning method, DRWMs is proposed. The combination of the real-time Wi-Fi FTM ranging model and the multi-sensor estimation method effectively improves the accuracy and stability of final dead reckoning.
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