Time Of Arrival Measurements Research Articles

Fingerprint localization based on hybrid TOA, AOA, and RSS measurements

This paper presents a novel joint TOA-AOA-RSS fingerprint localization method aimed at reducing the necessity for collecting extensive fingerprint data for database construction. Initially, The Time-of-Arrival(TOA) is employed for coarse localization to narrow down the fingerprint database. Subsequently, Angle-of-Arrivals(AOAs) and Received Signal Strengths(RSSs) were used as feature parameters to construct the fingerprint database together with the coarse localization coordinates obtained from the TOA. Finally, a matching algorithm is utilized to determine the coordinate of the localization point. Additionally, we introduce an improved self adaptive weighted K nearest neighbor (ISAWKNN) algorithm is proposed based on Hybrid TOA,AOA, and RSS measurements. Simulation results illustrate the proposed algorithm improving the localization accuracy.

Picosecond timing performances of the FERS time unit

Next-generation high-energy physics experiments will employ high-granularity detectors with thousands of readout channels, necessitating the use of low-power, compact ASICs. The CAEN FrontEnd Readout System (FERS) 5200 integrates these ASICs within small, synchronizable, and distributable systems featuring both Front and Back Ends. The A5203 FERS module incorporates the recently released CERN picoTDC ASIC, enabling high-resolution timing measurements for Time of Arrival (ToA) and Time over Threshold (ToT).In this work, we analyze the performance of the A5203 unit, which has a 3.125 ps least significant bit (LSB), delivering ToA measurements with an RMS resolution of approximately 7 ps for signals of fixed amplitude, and approximately 20 ps RMS for input signals with variable amplitude over a 50 dB dynamic range over a single board. The amplitude-dependent walk effect is corrected using ToT, which, in addition to walk correction, is also utilised for signal amplitude reconstruction and background reduction.The A5203 has been successfully applied across various experimental and industrial contexts. In the concluding section of this paper, we will discuss its application within the ProVision project: a PET scanner specialised in imaging aggressive prostate cancer at an early-stage.

Wireless sensor localization based on distance optimization and assistance by mobile anchor nodes: a novel algorithm.

Wireless sensor networks (WSNs) have wide applications in healthcare, environmental monitoring, and target tracking, relying on sensor nodes that are joined cooperatively. The research investigates localization algorithms for both target and node in WSNs to enhance accuracy. An innovative localization algorithm characterized as an asynchronous time-of-arrival (TOA) target is proposed by implementing a differential evolution algorithm. Unlike available approaches, the proposed algorithm employs the least squares criterion to represent signal-sending time as a function of the target position. The target node's coordinates are estimated by utilizing a differential evolution algorithm with reverse learning and adaptive redirection. A hybrid received signal strength (RSS)-TOA target localization algorithm is introduced, addressing the challenge of unknown transmission parameters. This algorithm simultaneously estimates transmitted power, path loss index, and target position by employing the RSS and TOA measurements. These proposed algorithms improve the accuracy and efficiency of wireless sensor localization, boosting performance in various WSN applications.

Graph-Based vs. Error State Kalman Filter-Based Fusion of 5G and Inertial Data for MAV Indoor Pose Estimation

5G New Radio Time of Arrival (ToA) data has the potential to revolutionize indoor localization for micro aerial vehicles (MAVs). However, its performance under varying network setups, especially when combined with IMU data for real-time localization, has not been fully explored so far. In this study, we develop an Error State Kalman Filter (ESKF) and a Pose Graph Optimization (PGO) approach to address this gap. We systematically evaluate the performance of the derived approaches for real-time MAV localization in realistic scenarios with 5G base stations in Line-Of-Sight (LOS), demonstrating the potential of 5G technologies in this domain. In order to experimentally test and compare our localization approaches, we augment the EuRoC MAV benchmark dataset for visual-inertial odometry with simulated yet highly realistic 5G ToA measurements. Our experimental results comprehensively assess the impact of varying network setups, including varying base station numbers and network configurations, on ToA-based MAV localization performance. The findings show promising results for seamless and robust localization using 5G ToA measurements, achieving an accuracy of 15 cm throughout the entire trajectory within a graph-based framework with five 5G base stations, and an accuracy of up to 34 cm in the case of ESKF-based localization. Additionally, we measure the run time of both algorithms and show that they are both fast enough for real-time implementation.

Continuous TOA Measurement Based Single-Anchor Indoor Localization

On the premise of guaranteeing high-quality measurement data, active wireless localization (A-WL) locates the target by at least three anchor nodes (ANs) with known coordinates, while passive wireless localization (P-WL) requires more ANs. In addition, P-WL requires a cumbersome training process to maintain the robustness in application scenarios as much as possible. However, the optimal deployment of ANs is not an easy task, and the application scenario will not remain unchanged. Therefore, a lightweight localization system that satisfies the localization accuracy requirements and can be quickly deployed should be one of the preferred solutions for WL. In this paper, we propose a single-anchor localization system based on continuous time-of-arrival (TOA) measurement. Specifically, we fix the AN on the blade with uniform rotation, construct the time-length distribution map by using the cyclically varying TOA caused by blade rotation, and intercept it according to the rotation period. We extract the change angle and distance information from the intercepted data in real time to achieve single-anchor localization. Meanwhile, we also construct a support vector machine classifier to identify the line-of-sight state of each interception period to assist the angle estimation in harsh environments and further improve the adaptability of the system. Experimental results show that the line-of-sight recognition accuracy of higher than 92% under continuous movement, and the average localization error of less than 0.6m. The average localization error is less than 0.3m in the mixed motion state.

Robust ISAC Localization in Smart Cities: A Hybrid Network Approach for NLOS Challenges with Uncertain Parameters

Accurate localization holds paramount importance across many applications within the context of smart cities, particularly in vehicular communication systems, the Internet of Things, and Integrated Sensing and Communication (ISAC) technologies. Nonetheless, achieving precise localization remains a persistent challenge, primarily attributed to the prevalence of non-line-of-sight (NLOS) conditions and the presence of uncertainties surrounding key wireless transmission parameters. This paper presents a comprehensive framework tailored to address the intricate task of localizing multiple nodes within ISAC systems significantly impacted by pervasive NLOS conditions and the ambiguity of transmission parameters. The proposed methodology integrates received signal strength (RSS) and time-of-arrival (TOA) measurements as a strategic response to effectively overcome these substantial challenges, even in situations where the precise values of transmitting power and temporal information remain elusive. An approximation approach is judiciously employed to facilitate the inherent non-convex and NP-hard nature of the original estimation problem, resulting in a notable transformation, rendering the problem amenable to a convex optimization paradigm. The comprehensive array of simulations conducted within this study corroborates the efficacy of the proposed hybrid cooperative localization method by underscoring its superior performance relative to conventional approaches relying solely on RSS or TOA measurements. This enhancement in localization accuracy in ISAC systems holds promise in the intricate urban landscape of smart cities, offering substantial contributions to infrastructure optimization and service efficiency.

The FAST Galactic Plane Pulsar Snapshot Survey – III. Timing results of 30 newly discovered pulsars

ABSTRACT Timing observations are crucial for determining the basic parameters of newly discovered pulsars. Using the Five-hundred-meter Aperture Spherical radio Telescope (FAST) with the L-band 19-beam receiver covering the frequency range of 1.0–1.5 GHz, the FAST Galactic Plane Pulsar Snapshot (GPPS) Survey has discovered more than 600 faint pulsars with flux densities of only a few or a few tens of μJy at 1.25 GHz. To obtain accurate position, spin parameters and dispersion measure of a pulsar, and to calculate derived parameters such as the characteristic age and surface magnetic field, we collect available FAST pulsar data obtained either through targeted follow-up observations or through coincidental survey observations with one of the 19 beams of the receiver. From these data we obtain time of arrival (TOA) measurements for 30 newly discovered pulsars as well as for 13 known pulsars. We demonstrate that the TOA measurements acquired by the FAST from any beams of the receiver in any observation mode (e.g. the tracking mode or the snapshot mode) can be combined to get timing solutions. We update the ephemerides of 13 previously known pulsars and obtain the first phase-coherent timing results for 30 isolated pulsars discovered in the FAST GPPS Survey. Notably, PSR J1904+0853 is an isolated millisecond pulsar, PSR J1906+0757 is a disrupted recycled pulsar, and PSR J1856+0211 has a long period of 9.89 s that can constrain pulsar death lines. Based on these timing solutions, all available FAST data have been added together to obtain the best pulse profiles for these pulsars.

A feasibility study of 5G positioning with current cellular network deployment

This research examines the feasibility of using synchronization signals broadcasted by currently deployed fifth generation (5G) cellular networks to determine the position of a static receiver. The main focus lies on the analysis of synchronization among the base stations of a real 5G network in Milan, Italy, as this has a major impact on the accuracy of localization based on time of arrival measurements. Understanding such properties, indeed, is fundamental to characterize the clock drifts and implement compensation strategies as well as to identify the direct communication beam. The paper shows how the clock errors, i.e., inaccurate synchronization, among 5G base stations exhibit a significant bias, which is detrimental for precise cellular positioning. By compensating the synchronization errors of devices’ clocks, we demonstrate that it is in principle possible to localize a static user with an accuracy of approximately 8–10 m in non-obstructed visibility conditions, for urban and rural scenarios, using the deployed 5G network operating at 3.68 GHz and relying on broadcast signals as defined by 5G Release 15 standard. This work has been funded by the European Space Agency (ESA) Navigation Innovation and Support Program (NAVISP) Element 2 pillar which aims at improving the competitiveness of the industry of the participating States in the global Positioning, Navigation and Timing (PNT) market.

Mitigating Sensor Motion Effect for AOA and AOA-TOA Localizations in Underwater Environments

The motion of sensors during the measurement period, if not accounted for, can degrade significantly the localization accuracy. This paper investigates the sensor motion effect for the positioning of an object, using angles of arrival only or together with time of arrival measurements. The biases from the AOA and TOA data models when ignoring the motion effect are examined. Positioning algorithms for AOA localization and mixed AOA-TOA localization that account for the motion effect are developed by the pseudo-linear formulation. The algorithms derived include the computationally attractive closed-form estimators and the noise resilient semidefinite programming solutions. The bias coming from the pseudo-linear formulation is analyzed in detail, and it can be subtracted from the closed-form solution to obtain a bias-suppressed estimate. Simulation validates the effectiveness of the proposed solutions in achieving the CRLB performance under Gaussian noise before the thresholding effect occurs.

Hybrid TOA-AOA WLS Estimator for Aircraft Network Decentralized Cooperative Localization

Cooperative localization is widely used to solve the network localization problem in global navigation satellite system (GNSS) denied environments. In particular, gathering the measurement results of all nodes on a specific node requires substantial time for aircraft networks. Therefore, methods simultaneously calculating all the target node positions are challenging to apply due to information delay. This study uses only two hops measurements information relying on the time of arrival (TOA) and angle of arrival (AOA) to propose a weighted least squares (WLS) method that decentralizes the calculation of a specific single target node position in a 3D environment. Moreover, the effect of TOA and AOA measurement errors on localization accuracy is analyzed based on the geometric relationship. Consequently, a novel weight-factor calculation method is designed. The simulation results show that the proposed cooperative localization method can improve localization accuracy compared with the decentralized non-cooperative method. Furthermore, the proposed hybrid approach provides superior localization accuracy than the weight-factor calculation method which only considers the distance.

Fundamental Limits of Doppler Shift-Based, ToA-Based, and TDoA-Based Underwater Localization

Dear Editor, This paper is concerned with the underwater localization based on acoustic signals. Specifically, we will focus on the search of an underwater target that can constantly broadcast a beacon signal, such as a black box. Common measurements for localization are Doppler shift [1], time of arrival (ToA) [2]–[4], time difference of arrival (TDoA) [5], [6], angle of arrival (AoA) [7], etc. In this paper we will investigate the fundamental limits of Doppler shift-Based, ToA-Based, TDoA-based underwater localization. Note that AoA is not covered, because Doppler shift can be viewed as one type of AoA. The discussion will focus on short-baseline positioning with a mobile anchor, i.e., an autonomous underwater vehicle (AUV). Due to the large distance and the limited battery life of the AUV, the target is quite likely to lie outside the convex hull of the AUV's trajectory. In such cases, we will show that accurate localization is almost impossible by exclusively dependent on a single type of measurements. However, system performance will be significantly improved by combing Doppler shift with ToA or TDoA measurements. The reason for such improvement will be unveiled theoretically and numerically in this letter.

Wide-band Timing of the Parkes Pulsar Timing Array UWL Data

In 2018 an ultra–wide-bandwidth low-frequency (UWL) receiver was installed on the 64 m Parkes Radio Telescope, enabling observations with an instantaneous frequency coverage from 704 to 4032 MHz. Here we present the analysis of a 3 yr data set of 35 ms pulsars observed with the UWL by the Parkes Pulsar Timing Array, using wide-band timing methods. The two key differences compared to typical narrowband methods are (1) generation of two-dimensional templates accounting for pulse shape evolution with frequency and (2) simultaneous measurements of the pulse time of arrival (TOA) and dispersion measure (DM). This is the first time that wide-band timing has been applied to a uniform data set collected with a single large fractional bandwidth receiver, for which such techniques were originally developed. As a result of our study, we present a set of profile evolution models and new timing solutions, including initial noise analysis. Precision of our TOA and DM measurements is in the range of 0.005–2.08 μs and (0.043–14.24) × 10−4 cm−3 pc, respectively, with 94% of the pulsars achieving a median TOA uncertainty of less than 1 μs.

A two-steps close-form positioning estimator based on AOA/TOA measurements

ABSTRACT Positioning is an increasingly important area in wireless networks. Time of arrival (TOA) and angle of arrival (AOA) are two of the most widely used physical parameters in positioning. In this letter, a two-step closed-form positioning method based on TOA and AOA measurements is proposed. Through the application of the least squares estimate to the original maximum likelihood optimization problem, a coarse estimate of the source node is obtained. We next compute a highly helpful weight, which is the inverse of the covariance matrix obtained by applying the predicted source node position. Finally, the weighted least squares method is used to estimate the final position of the source node. The proposed estimator has good estimation accuracy and low complexity and is very close to Cramer-Rao Lower Bounds, according to simulations.

Robust Vehicle Positioning Based on Multi-Epoch and Multi-Antenna TOAs in Harsh Environments

For radio-based time-of-arrival (TOA) positioning systems applied in harsh environments, obstacles in the surroundings and on the vehicle itself will block the signals from the anchors, reduce the number of available TOA measurements and thus degrade the localization performance. Conventional multi-antenna positioning technique requires a good initialization to avoid local minima, and suffers from location ambiguity due to insufficient number of TOA measurements and/or poor geometry of anchors at a single epoch. In this paper, taking advantage of the multi-epoch and multi-antenna (MEMA) TOA measurements bridged by inter-epoch constraints to utilize more information and improve the geometry of visible anchors, we propose a new positioning method, namely MEMA-TOA method. A new initialization method based on semidefinite programming (SDP), namely MEMA-SDP, is first designed to address the initialization problem of the MEMA-TOA method. Then, an iterative refinement step is developed to obtain the optimal positioning result based on the MEMA-SDP initialization. We derive the Cramér-Rao lower bound (CRLB) to analyze the accuracy of the new MEMA-TOA method theoretically, and show its superior positioning performance over the conventional single-epoch and multi-antenna (SEMA) localization method. Simulation results in harsh environments demonstrate that i) the new MEMA-SDP provides an initial estimation that is close to the real location, and empirically guarantees the global optimality of the final refined positioning solution, and ii) compared with the conventional SEMA method, the new MEMA-TOA method has higher positioning accuracy without location ambiguity, consistent with the theoretical analysis.

Crilin: CRystal calorImeter with Longitudinal InformatioN for a future Muon Collider

In modern experiment, a high granularity is required in order to distinguish signal particles from background and to solve the substructures necessary for jet identification. Time of arrival measurements in the calorimeter could play an important role in HL-LHC, since a high number of pile-up collisions is expected, and the timing could be used to assign clusters to the corresponding interaction vertex. In a Muon Collider, the timing could be used to remove signals produced by beam-induced background, asynchronous with respect to the bunch crossing. The calorimeter energy resolution is also fundamental to measure the kinematic properties of jets: a finely segmented calorimeter design should be favored in order to solve the jet substructure. However, this contrasts with the requirement for high timing resolution even for signal events involving low energy deposits, such as in the case of high impulse muons. Our proposed design, the Crilin calorimeter, is a semi-homogeneous calorimeter based on Lead Fluoride (PbF2) Crystals readout by surface-mount UV-extended Silicon Photomultipliers (SiPMs). In this paper, the development of a small prototype consisting of 2 layers of 3 × 3 crystals each is reported along with the relative results.

Sequential Doppler-Shift-Based Optimal Localization and Synchronization With TOA

Doppler shift is an important measurement for localization and synchronization (LAS), and is available in various practical systems. Existing studies on LAS techniques in a time-division broadcast LAS system (TDBS) only use sequential time-of-arrival (TOA) measurements from the broadcast signals. In this article, we develop a new optimal LAS method in the TDBS, namely, LAS-SDT, by taking advantage of the sequential Doppler shift and TOA measurements. It achieves higher accuracy compared with the conventional TOA-only method for user devices (UDs) with motion and clock drift. Another two variant methods, LAS-SDT-v for the case with UD velocity aiding and LAS-SDT-k for the case with UD clock drift aiding, are developed. We derive the Cramér–Rao lower bound (CRLB) for these different cases. We show analytically that the accuracies of the estimated UD position, clock offset, velocity, and clock drift are all significantly higher than those of the conventional LAS method using TOAs only. Numerical results corroborate the theoretical analysis and show the optimal estimation performance of the LAS-SDT.

Information Fusion Strategies for Collaborative Inertial Radio SLAM

Information fusion strategies for vehicles navigating while aiding their inertial navigation systems (INSs) with terrestrial signals of opportunity (SOPs) are developed and studied. The following problem is considered. Multiple navigating vehicles with access to global navigation satellite system (GNSS) signals are aiding their on-board INSs with GNSS pseudoranges. While navigating, vehicle-mounted receivers draw pseudorange measurements from terrestrial SOPs (e.g., AM/FM radio, digital television, cellular) with unknown emitter positions and unknown and unsynchronized clocks. The vehicles share INS data and SOP pseudoranges to collaboratively estimate the SOPs’ states through an extended Kalman filter using tight coupling. After some time, GNSS signals become unavailable, at which point the navigating vehicles use shared INS and SOP information to continue navigating in a collaborative inertial radio simultaneous localization and mapping (CIRSLAM) framework. This paper develops such CIRSLAM framework and synthesizes what SOP and INS information should be shared between collaborators. Two information fusion strategies are compared: 1) sharing time-of-arrival (TOA) measurements from SOPs; 2) sharing time-difference-of-arrival (TDOA) measurements taken with reference to an SOP. Next, a strategy to efficiently share INS information along with SOP information is discussed. Monte Carlo simulation results are presented that support the analytical findings that vehicles navigating in a CIRSLAM framework, while sharing and fusing SOP TOA measurements, produce a smaller or equal estimation error covariance compared to fusing SOP TDOA measurements. Experimental results are presented demonstrating two unmanned aerial vehicles (UAVs) navigating in a CIRSLAM framework with SOP TOA measurements from terrestrial cellular towers. The final UAVs’ localization error after 30 seconds of GPS unavailability were reduced compared to using an INS alone from around 55 m to around 6 m.

Testing the non-circularity of the spacetime around Sagittarius A* with orbiting pulsars

Abstract A disformal Kerr black hole solution is a rotating black hole solution in a modified gravity theory which breaks the circular condition of spacetime differently from the case of the Kerr spacetime. In this paper, assuming that Sagittarius A* (Sgr A*) is a disformal Kerr black hole, we examine the potential to test the spacetime geometry with a hypothetical pulsar whose orbital elements are similar to those of the S2/S0-2 star. By numerically solving the equations of motion for the pulsar and photons emitted from it, we calculate the apparent position of the pulsar and the time of arrival (TOA) of the emitted pulse signals. Our analysis shows that the magnitude of the difference in the TOAs reaches the order of 10 ms if the deviation from the Kerr spacetime is significant. The time difference is mainly caused by the non-circularity of the spacetime at the 1.5 post-Newtonian order. The accuracy of the TOA measurement by a future radio telescope named the Square Kilometer Array (SKA) is between about 0.1 ms and 10 ms for a normal pulsar. Thus, we expect that the SKA can distinguish a disformal Kerr black hole from a Kerr black hole through the non-circularity of the spacetime around Sgr A*.

Vehicle Localization Using Doppler Shift and Time of Arrival Measurements in a Tunnel Environment.

Most applications and services of Cooperative Intelligent Transport Systems (C-ITS) rely on accurate and continuous vehicle location information. The traditional localization method based on the Global Navigation Satellite System (GNSS) is the most commonly used. However, it does not provide reliable, continuous, and accurate positioning in all scenarios, such as tunnels. Therefore, in this work, we present an algorithm that exploits the existing Vehicle-to-Infrastructure (V2I) communication channel that operates within the LTE-V frequency band to acquire in-tunnel vehicle location information. We propose a novel solution for vehicle localization based on Doppler shift and Time of Arrival measurements. Measurements performed in the Beveren tunnel in Antwerp, Belgium, are used to obtain results. A comparison between estimated positions using Extended Kalman Filter (EKF) on Doppler shift measurements and individual Kalman Filter (KF) on Doppler shift and Time of Arrival measurements is carried out to analyze the filtering methods performance. Findings show that the EKF performs better than KF, reducing the average estimation error by 10 m, while the algorithm accuracy depends on the relevant RF channel propagation conditions and other in-tunnel-related environment knowledge included in the estimation. The proposed solution can be used for monitoring the position and speed of vehicles driving in tunnel environments.

Local Strong Convexity of Source Localization and Error Bound for Target Tracking under Time-of-Arrival Measurements

In this paper, we consider a time-varying optimization approach to the problem of tracking a moving target using noisy time-of-arrival (TOA) measurements. Specifically, we formulate the problem as that of sequential TOA-based source localization and apply online gradient descent (OGD) to it to generate the position estimates of the target. To analyze the tracking performance of OGD, we first revisit the classic least-squares formulation of the (static) TOA-based source localization problem and elucidate its estimation and geometric properties. In particular, under standard assumptions on the TOA measurement model, we establish a bound on the distance between an optimal solution to the least-squares formulation and the true target position. Using this bound, we show that the loss function in the formulation, albeit non-convex in general, is locally strongly convex at its global minima. To the best of our knowledge, these results are new and can be of independent interest. By combining them with existing techniques from online strongly convex optimization, we then establish the first non-trivial bound on the cumulative target tracking error of OGD. Our numerical results corroborate the theoretical findings and show that OGD can effectively track the target at different noise levels.