Keypoint
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Pedestrian positionin
Benefit
When a model-based positioning method is used, pedestrian position usually is computed by trilateration. The pedestrian-anchor distances can be estimated by different methods, as follows:
(i) Signal-strength-based method. RSSI is a measurement of RF power at a receiver. The path-loss model indicating the attenuation of RSSI with respect to distance is often used to predict distance from RSSI, although its accuracy is greatly affected by the impact of shadowing and multipath fading.
In a wideband system, multipath signals and the direct wave arrive at a receiver at different timing, and it is possible to estimate the distance from the strength of the direct wave [6], [14], [15]. In this way, the pedestrian-anchor distance is more accurate than that by RSSI. But its performance is limited by time resolution when a reflected wave overlaps the direct one.
[6] S. Tang and S. Obana, “Improving performance of pedestrian positioning by using vehicular communication signals,” IET Intelligent Transport Systems, vol. 12, no. 5, pp. 366–374, 2018.
[14] S. Sen, J. Lee, K.-H. Kim, and P. Congdon, “Avoiding multipath to revive inbuilding WiFi localization,” in Proceeding of the 11th Annual International Conference on Mobile Systems, Applications, and Services, ser. MobiSys ’13, 2013, pp. 249–262.
[15] Z. Yang, Z. Zhou, and Y. Liu, “From RSSI to CSI: Indoor localization via channel response,” ACM Comput. Surv., vol. 46, no. 2, Dec. 2013. [Online]. Available: https://doi.org/10.1145/2543581.2543592
(ii) Time-based method. It is possible to measure the time-of-arrival (ToA) at a receiver. In order to avoid the synchronization between transmitter and receiver, time-of-flight is estimated by exchanging a sequence of messages containing ToA between a transmitter and a receiver, in FTM (fine time measurement) based method standardized in IEEE 802.11mc. This, however, causes a large delay in position computation [16] (and also much overhead). It is shown that FTM has a similar distance error behavior as that by RSSI in a multipath rich environment [17], and a correction is required for each pair of transmitter and receiver [18].
To avoid the synchronization between transmitters and receivers, another method is to compute the TDoA. In [19], a transmitter transmits an IEEE 802.11g signal, and ToA is estimated at the receiver side, using the long training sequence. Then, TDoA is used to compute the transmitter position.
[16] L. Banin, O. Bar-Shalom, N. Dvorecki, and Y. Amizur, “High-accuracy indoor geolocation using collaborative time of arrival,” IEEE, Tech. Rep. IEEE 802.11-17/1397R0, 2017.
[17] M. Bullmann, T. Fetzer, F. Ebner, M. Ebner, F. Deinzer, and M. Grzegorzek, “Comparison of 2.4 GHz WiFi FTM- and RSSIbased indoor positioning methods in realistic scenarios,” Sensors, vol. 20, no. 16, 2020. [Online]. Available: https://www.mdpi.com/1424-8220/20/16/4515
[18] J. Choi, “Enhanced Wi-Fi RTT ranging: A sensor-aided learning approach,” IEEE Transactions on Vehicular Technology, pp. 1–10, 2022.
[19] A. Makki, A. Siddig, M. Saad, J. R. Cavallaro, and C. J. Bleakley, “Indoor localization using 802.11 time differences of arrival,” IEEE Transactions on Instrumentation and Measurement, vol. 65, no. 3, pp. 614–623, 2016.
(iii) Phase-based method. In order to measure the radio wave propagation distance more accurately, in the RFID field, the property that the phase increases linearly with the radio wave propagation distance is exploited [11], [20]. Each time one frequency is used and it takes time to switch frequencies and measure phase variation of each frequency successively. To further improve the accuracy, a combination of TDoA and PDoA is studied in [12].
[11] A. Povalac and J. Sebesta, “Phase difference of arrival distance estimation for RFID tags in frequency domain,” in 2011 IEEE International Conference on RFID-Technologies and Applications, 2011, pp. 188–193.
[12] H. Chen, T. Ballal, N. Saeed, M.-S. Alouini, and T. Y. Al-Naffouri, “A joint TDOA-PDOA localization approach using particle swarm optimization,” IEEE Wireless Communications Letters, vol. 9, no. 8, pp. 1240–1244, 2020.
[20] G. von Zengen, Y. Schroder, S. Rottmann, F. Busching, and L. C. Wolf, “No-cost distance estimation using standard WSN radios,” in IEEE INFOCOM 2016 – The 35th Annual IEEE International Conference on Computer Communications, 2016, pp. 1–9.
To improve the efficiency of measuring phases, in this work, we focus on using OFDM signals to estimate the phases of multiple frequencies simultaneously, and solve potential problems.
Phase information is more resistant to noise, compared with RSSI that depends on radio wave attenuation characteristics. By the double phase difference, error factors such as OFDM modulation data and carrier frequency variations can be mitigated, and ISI can be avoided by adjusting the sampling time. Furthermore, it is confirmed that multipath waves can be suppressed by using multiple frequencies at the same time, and the result in the multipath-rich environment is promising.