Conventional Ultra-Wideband (UWB) localization systems typically require multiple anchors for effective tag localization. However, recent studies have demonstrated that multi-path components (MPCs) can provide additional information for indoor localization by introducing the concept of virtual anchors (VAs), even with a single-anchor setup. This work proposes a novel single-anchor UWB simultaneous localization and mapping (SLAM) system that requires no prior information on the anchor position or floor plan. The system uses measurements of the phase difference of arrival (PDOA) by the tag, and by fusing distance and PDOA estimations with inaccurate tag movement measurements the system refines the tag trajectory and estimates the anchor and VA positions. Simulations and experiments demonstrate that the proposed system can accurately estimate wall positions as well as significantly improve the tag localization.

Indoor localization based on Bluetooth Low Energy (BLE) is traditionally implemented by matching Received Signal Strength (RSS) fingerprints of nearby BLE nodes. Depending on the node density, pure RSS-based BLE localization only provides room-level or zone-level accuracies. For pedestrian tracking, BLE-based RSS fingerprinting is often fused with Pedestrian Dead Reckoning (PDR) using Inertial Measurement Units (IMU), which can provide up to $1-2 \mathrm{~m}$ accuracy. Recently, a phase-based BLE ranging method has been developed, which can accurately measure the distance between two BLE devices. Initial experiments on a moving platform showed promising results for accurate localization. In this work, the feasibility of this technology for pedestrian tracking is evaluated. On-body phase-based BLE and IMU measurements are performed in an industrial lab environment with four BLE anchors. A hybrid Particle Filter (PF) algorithm is designed, which fuses phase-based BLE ranging, PDR, and a range correction algorithm. Our proposed PF algorithm achieves a median and p75 error of $0.70 \mathbf{m}$ and $1.03 \mathbf{~ m}$ respectively, which outperforms traditional RSS-based (hybrid) BLE localization algoritms.

The leading edge of a transmitted pulse shape plays an important role in the estimation of the Time of Arrival (ToA) of the pulse by a receiver. This is particularly the case for indoor, multipath environments, in which the trailing edge and to some extent the peak of the pulse may well be corrupted by following multipath components. It is therefore proposed that an asymmetric Ultra-Wide Band (UWB) pulse shape is used with a steep leading edge, generated by a modest precursor pulse with the opposite carrier phase to improve close-in multipath robustness. An integrated circuit implementation and experiments show such a pulse can meet the spectrum mask and improve the ToA measurement performance.

This paper presents a method for estimating the time of arrival (ToA) of long term evolution (LTE) signals received on multiple separate transmission bands by the same base station (BS) mast. By exploiting the overall bandwidth occupied by the different signals and the correlation between the corresponding channel impulse responses, a higher precision is achieved with respect to the usually adopted single-band approach whenever the time-correlation among the bands is sufficiently high. The ToA estimation is carried out by generalizing the space-alternating generalized expectation-maximization (SAGE) algorithm to the multi-band context, proving that the availability of multiple bands provides a reduced standard deviation for the estimated ToA, with a limited increase of the computational cost. The main analyzed issue consists in the management of the asynchrony between transmitters belonging to distinct cellular operators, which is addressed by developing a suitable method to combine the contributions provided by the different bands. The method is validated by simulations in dual- and tri-band scenarios, and is further applied to real dual-band signals measured through a portable setup and experimentally acquired from an LTE BS mast covering multiple cells.

This paper describes the use of standard LTE communications signals to perform positioning indoors, despite the difficult propagation conditions in such environments that require a number of strong signals and a wide measurement bandwidth. Experiments show that the CRS transmissions embedded in normal LTE downlink signals from multiple network operators' base stations can together be used to perform horizontal localization indoors around a building, with an accuracy of around 15m for full bandwidth LTE signals. A reference unit (LMU) is required. Alternatively and with more reference measurement units, 3D positioning can be performed using the uplink signals transmitted by the target LTE modem, and it is shown that a set of DM-RS transmissions embedded within normal uplink communications traffic to its base station can be combined to also give measurements of signals with a wide effective bandwidth.

This paper discusses the use of the Space-Alternating Generalized Expectation-maximization (SAGE) algorithm for Time of Arrival (ToA) estimation in Orthogonal Frequency Division Multiplexing (OFDM) systems. This algorithm, which is an extension of the expectation-maximization approach, can exploit the intrinsic properties of a multi-carrier OFDM system to achieve the estimation of a number of parameters of each incoming signal replica, such as its amplitude, ToA, Doppler shift, and angle of arrival. The SAGE method can also be easily tailored to estimate only a desired subset of these parameters. Accordingly, this study focuses on the sole ToA estimation, but extending the SAGE functionalities to dual-band OFDM systems. This extension is achieved by exploiting the availability at the receiver of more than one band from the same transmitter, and combining the derived channel information to increase the bandwidth available for estimation. It will be shown that, in highly correlated scenarios, the performance of the SAGE algorithm for ToA estimation in a dual-band system is comparable to that of a single-band system with equivalent total bandwidth.

This paper presents an experiment using real Long-Term Evolution (LTE) signals to extend positioning from outdoors to indoors. LTE signals are of interest for positioning applications because of their availability indoors, where GNSS signal reception is limited. Different approaches for time of arrival (TOA) extraction are evaluated for their positioning performance, combined with an extended Kalman filter (EKF) for movement tracking. The paper shows that the performance is surprisingly good, with high visibility of cellular signals even in the difficult indoor test environment, and with a positioning error once indoors smaller than 8m in 50% of cases.

This paper proposes an algorithm for the estimation and tracking of the direct path (DP) time of arrival (TOA) of the signals received from 4G long term evolution (LTE) cellular base stations (BSs) in a mobile multipath environment. This is important for TOA-based ranging measurements, which may be exploited for positioning applications. A sub-space approach is used for the estimation of the multipath time of arrival, and a state-space approach is exploited for tracking the direct path. The developed framework is applied to real LTE signals collected using a portable experimental setup during a car drive in the town of Rapperswil, Switzerland. The pseudoranges derived from the tracking of the DP TOA are then compared to the ranges from the considered LTE base stations calculated using GPS, demonstrating the effectiveness of the proposed approach.

This letter characterizes the error performance of realistically modelled orthogonal frequency division multiplexing (OFDM) signals, when their time of arrival has to be estimated in an additive white Gaussian noise channel. In particular, different power distributions on the available sub-carriers of the OFDM signal are considered, and bounds on the corresponding root mean square estimation error (RMSEE) are evaluated. The tools used for such purpose are the widely adopted Cramér-Rao bound and the Ziv-Zakai bound, which is tight in a wide range of signal-to-noise ratio (SNR) values. The presented analysis reveals that, for a given signal bandwidth, a proper power distribution on the OFDM sub-carriers is crucial for achieving a good performance in the low to medium SNR region, where the RMSEE curve exhibits the typical threshold behavior. Moreover, a trade-off between asymptotic and threshold performance is identified, thanks to the adoption of a novel performance figure, which directly describes the threshold RMSEE behavior.