Probabilistic Positioning Via Ray Tracing With Noisy Angle of Arrival Measurements
Abstract: We consider the positioning problem in non line-of-sight (NLoS) situations, where several base stations (BS) try to locate a user equipment (UE) based on uplink angle of arrival (AoA) measurements and a digital twin of the environment. Ray launching in a Monte Carlo manner according to the AoA statistics enables to produce a map of points for each BS. These points represent the intersections of the rays with a xy plane at a given user equipment (UE) elevation. We propose to fit a parametric probability density function (pdf), such as a Gaussian mixture model (GMM), to each map of points. Multiplying the obtained pdfs for each BS enables to compute the position probability of the UE. This approach yields an algorithm robust to a reduced number of launched rays. Moreover, these parametric pdfs may be fitted and stored in an offline phase such that ray tracing can be avoided in the online phase. This significantly reduces the computational complexity of the positioning method.
- S. Kikuchi, A. Sano, and H. Tsuji, “Blind Mobile Positioning in Urban Environment Based on Ray-Tracing Analysis,” EURASIP Journal on Applied Signal Processing, Article number: 038989, Jan. 2006.
- F. Kong, N. Zheng, G. Liu, and X. Ren, “Position Orientating PathReverse Ray Tracing Algorithm Based on Cluster Analysis,” in Proc. IEEE International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), Shanghai, China, June 2016.
- V. Nguyen, V. Corlay, and N. Gresset, “Probabilistic ray-tracing aided positioning at mmWave frequencies,” International Conference on Indoor Positioning and Indoor Navigation, Nuremberg, Germany, Sept. 2023.
- A. Roche, “EM algorithm and variants: An informal tutorial,” 2011. arXiv:1105.1476
- D. Liu, K. Liu, Y. Ma, and J. Yu, “Joint TOA and DOA Localization in Indoor Environment Using Virtual Stations,” IEEE Communications Letters, vol. 18, no. 8, pp. 1423-1426, Aug. 2014.
- S. Wielandt and L. De Strycker, “Indoor Multipath Assisted Angle of Arrival Localization,” Sensors, vol. 17, no. 11, Nov. 2017.
- 5G-ACIA RP-181521, “LS on Channel Model for Indoor Industrial Scenarios,” Meeting number 81, Gold Coast, AU, Sept 2018. Available at: https://www.3gpp.org/ftp/TSG_RAN/TSG_RAN/TSGR_81/Docs/
- 3GPP TR 38.843, “Study on Artificial Intelligence (AI)/Machine Learning (ML) for NR air interface,” version 1.1.0, Meeting number 114bis, Nov. 2023.
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