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1. Millimeter Wave Position Location using Multipath Differentiation for 3GPP using Field Measurements

   Ojas Kanhere, Theodore S. (December 2020, 2020 IEEE Global Communciations conference)

   null (Ed.)

   3GPP air interface standards support meter-level position location of a user in a cellular network. With wider bandwidths and narrow antenna beamwidths available at mmWave frequencies, cellular networks now have the potential to provide sub-meter position location for each user. In this work, we provide an overview of 3GPP position location techniques that are designed for line-of-sight propagation. We discuss additional measurements required in the 3GPP standard that enable multipath-based non-line-of-sight position location. Further, we validate the concepts in this paper by using field data to test a map-based position location algorithm in an indoor office environment which has dimensions of 35 m by 65.5 m. We demonstrate how the fusion of angle of arrival and time of flight information in concert with a 3-D map of the office provides a mean accuracy of 5.72 cm at 28 GHz and 6.29 cm at 140 GHz, over 23 receiver distances ranging from 4.2 m to 32.3 m, using a single base station in line-of-sight and non-line-of-sight. We also conduct a theoretical analysis of the typical error experienced in the map-based position location algorithm and show that the complexity of the map-based algorithm is low enough to allow real-time implementation. 

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2. Map-Assisted Millimeter Wave Localization for Accurate Position Location

   https://doi.org/10.1109/globecom38437.2019.9013365  

   Kanhere, Ojas; Ju, Shihao; Xing, Yunchou; Rappaport, Theodore S. (December 2019, 2019 IEEE Global Communications Conference)

   null (Ed.)

   Accurate precise positioning at millimeter wave frequencies is possible due to the large available bandwidth that permits precise on-the-fly time of flight measurements using conventional air interface standards. In addition, narrow antenna beamwidths may be used to determine the angles of arrival and departure of the multipath components between the base station and mobile users. By combining accurate temporal and angular information of multipath components with a 3- D map of the environment (that may be built by each user or downloaded a-priori), robust localization is possible, even in non-line-of-sight environments. In this work, we develop an accurate 3-D ray tracer for an indoor office environment and demonstrate how the fusion of angle of departure and time of flight information in concert with a 3-D map of a typical large office environment provides a mean accuracy of 12.6 cm in line-of-sight and 16.3 cm in non-line-of-sight, over 100 receiver distances ranging from 1.5 m to 24.5 m using a single base station. We show how increasing the number of base stations improves the average non-line-of-sight position location accuracy to 5.5 cm at 21 locations with a maximum propagation distance of 24.5 m. Index Terms—localization; positioning; position location; navigation; mmWave; 5G; ray tracing; site-specific propagation; map-based 

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3. Outdoor sub-THz Position Location and Tracking using Field Measurements at 142 GHz

   https://doi.org/10.1109/ICC42927.2021.9500482  

   Kanhere, O; Rappaport, T.S. (June 2021, 2021 IEEE International Conference on Communications (ICC), June 2021)

   AbstractÐFuture sub-THz cellular deployments may be utilized to complement the coverage of the global positioning system (GPS) and provide centimeter-level accuracy. In this work, we use measurement data at 142 GHz to test a map-based position location algorithm in an outdoor urban microcell (UMi) environment. We utilize an extended Kalman filter (EKF) to track the position of the user equipment (UE) along a rectangular track, with the transmitter-receiver separation distances varying from 24.3 m to 52.8 m. The position and velocity of the UE are tracked by the EKF, with measurements of the angle of arrival and time of flight information obtained along an outdoor track, to provide a mean accuracy of 24.8 cm at 142 GHz, over 34 UE locations, using a single base station in line-of-sight and non-line-of-sight. 

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4. Machine learning regression-based RETRO-VLP for real-time and stabilized indoor positioning

   https://doi.org/10.1007/s10586-022-03884-w  

   Alenezi, Ali H.; Nazzal, Mahmoud; Sawalmeh, Ahmed; Khreishah, Abdallah; Shao, Sihua; Almutiry, Muhannad (December 2022, Cluster Computing)

   Many real-world applications require real-time and robust positioning of Internet of Things (IoT) devices. In this context, visible light communication (VLC) is a promising approach due to its advantages in terms of high accuracy, low cost, ubiquitous infrastructure, and freedom from RF interference. Nevertheless, there is a growing need to improve positioning speed and accuracy. In this paper, we propose and prototype a VLC-based positioning solution using retroreflectors attached to the IoT device of interest. The proposed algorithm uses the retroreflected power received by multiple photodiodes to estimate the euclidean and directional coordinates of the underlying IoT device. In particular, the relative relationship between reflected light magnitude and reflected power is used as input to trainable machine learning regression models. Such models are trained to estimate the coordinates. The proposed algorithm excels in its simplicity and fast computation. It also reduces the need for sensory devices and active operation. Additionally, after regression, Kalman filtering is applied as a post-processing operation to further stabilize the obtained estimates. The proposed algorithm is shown to provide stable, accurate, and fast. This has been verified by extensive experiments performed on a prototype in real-world environments. Experiments confirm a high level of positioning accuracy and the added benefit of Kalman filtering stabilization. 

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5. Spatio‐Temporal Evolution of Mid‐Latitude GPS Scintillation and Position Errors During the May 2024 Solar Storm

   https://doi.org/10.1029/2025JA033839  

   Younas, Waqar; Nishimura, Yukitoshi; Liao, Weixuan; Semeter, Josh L; Mrak, Sebastijan; Morton, Y Jade; Groves, Keith M (June 2025, Journal of Geophysical Research: Space Physics)

   Abstract This study investigates impacts of the May 2024 superstorm on the mid‐latitude Global Positioning System (GPS) scintillation and position errors. Using 1‐Hz GPS receiver data, we identified position errors in PPP mode reaching up to 70 m in the Central United States during the storm main phase on May 10. The PPK solution becomes unstable following the arrival of storm and lasted till the recovery phase, coinciding with reported GPS outages of farming equipment. The large position errors were attributed to strong scintillation and carrier phase cycle slips around the equatorward boundary of the ionosphere trough, where large total electron content (TEC) gradients and irregularities were present. In the Southwestern United States, position errors of 10–20 m were associated with the storm‐enhanced density and equatorial ionization anomaly. Scintillation and cycle slips in this region were minor, and bending of the GPS signal paths (refractive effect) is suggested to cause the position errors. PPP outages were also associated with sudden changes in the geometric distributions of available GPS satellites used in position calculations. On May 11, energetic particle precipitation during substorms led to abrupt jumps in TEC and scintillation, resulting in rapidly evolving position errors of up to 10 m. These findings highlight the critical role of storm‐time plasma transport, precipitation, and irregularity formation in degrading GPS performance. The study underscores the need for accurate ionospheric state specification, improved signal processing technique, real‐time ionospheric corrections, and optimized satellite selection algorithms, to enhance navigation resilience during severe space weather events. 

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