JOINT POSITIONING AND TRACKING VIA NR SIDELINK
(Submitted to IEEE Wireless Communications Magazine)
In the above video, time difference of arrival (TDoA) and angle of arrival (AoA) measurements are utilized in an extended Kalman filter (EKF) for joint positioning and tracking of both target and anchor nodes.
CHANNEL PARAMETER ESTIMATINO AND TX POSITIONING WITH MULTI-BEAM FUSION
(Submitted to IEEE Transactions on Wireless Communications)
In this demonstration, the TX node that is attached to a vehicle is moving along a pre-determined trajectory and following a realistic acceleration profile. Every 100 ms, the TX transmits uplink sounding reference signals (SRS) through a short beam-sweep process exploiting only 8 beams at the TX-side. These signals are then received by the RX-nodes which are then estimating the considered channel parameters (ToA and DoA angles). The obtained parameter estimates are finally used in the TX positioning either in a single RX or in a centralised node depending on the amount of participating RX-nodes. The positioning performance of the proposed cascaded EKF algorithm is visualized for two different system setups. In the first setup, TX positioning is carried out using only a single RX, whereas in the second setup, ToA and DoA estimates from three RXs are fused in TX positioning. The participating RX nodes are all in line-of-sight (LoS) condition and their participation in the positioning phase is determined based on the observed SNRs.
POSITIONING OF A HIGH-SPEED TRAIN
(IEEE Communications Magazine)
In this demonstration, we illustrate the positioning performance of a high-speed train (HST) in a realistic 5G new-radio (NR) network building on the 3GPP specifications and 5G NR numerology. The velocity profile of the train is shown in the south-east corner, whereas the whole train trajectory is shown in the north-east corner together with the corresponding zoomed and more detailed illustrations on the left. Due to the geometry of the considerd HST scenario, the 95% confidence ellipse is relatively large in the perpendicular direction of the track when the remote radio heads (RRHs) are far away from the train, and hence, majority of the positioning error is stemming from this direction. However, the overall positioning performance is extremely high throughout the trajectory.
JOINT 3D POSITIONING AND BASE STATION ORIENTATION UNCERTAINTY ESTIMATION
(IEEE Transactions on Vehicular Technology)
In this demonstration, three user devices representing automated guided vehicles are moving in an open area in a realistic port environment. In the proposed framework, base stations (BSs) with 3-degree orientation uncertainties are first transmitting reference signals in a downlink through a set of fixed beams, after which the signals are received by the user devices in a beam-sweep process. Based on the considered beam-selection criterion, each device communicates the most significant beam reference signal received powers (BRSRPs) and the corresponding beam-indices back to the BS. Building on the proposed two-stage EKF-based estimation and tracking solution, these BRSRPs from all available BSs are fused into direction-of-departure (DoD) measurements, which are then used as measurements in joint device positioning and BS orientation uncertainty estimation.
DRONE POSITIONING (3D DEMO)
(IEEE Commun. Mag. 2018)
Example 3D positioning demonstration of a drone flying through the METIS Madrid Map. The trajectory of the drone contains a take-off in the beginning as well as a short landing in the middle of the trajectory. The continuous tracking of the drone is carried out by fusing either only direction of arrival (DoA) estimates or both DoA and time of arrival (ToA) estimates from two closest line of sight base stations in DoA-only or Pos&Sync extended Kalman filter (EKF), respectively.
JOINT 3D DRONE POSITIONING AND NETWORK SYNCHRONIZATION
(IEEE Commun. Mag. 2017)
An example where the 3D location of a drone is estimated and tracked while simultaneously synchronizing also the considered 5G network. In this solution, the direction of arrival (DoA) and time of arrival (ToA) measurements are first estimated at individual line of sight (LoS) access nodes (ANs) using an exteded Kalman filter (EKF), and these estimates are then fused into location and clock offset estimates in the second EKF-based estimation and tracking phase.
JOINT 3D VEHICLE POSITIONING AND NETWORK SYNCHRONIZATION USING UKF AND EKF
(IEEE GLOBECOM 2016)
A vehicle following a realistic empirical acceleration model is tracked through the METIS Madrid Map while simultaneously synchronizing the 5G radio network. In this solution, the direction of arrival (DoA) and time of arrival (ToA) measurements are first estimated at individual line of sight (LoS) access nodes (ANs), and these estimates are then fused into location and clock offset estimates in the second estimation and tracking phase. Both tracking phases are carried out using either an exteded Kalman filter (EKF) or unscented Kalman filter (UKF).
LOCATION-BASED BEAMFORMING IN MULTIUSER 5G NETWORK
(IEEE VTC Fall 2016)
BAn example where the locations of the users are utilized in location-based beamforming in the multiuser 5G METIS Madrid Map environment.