Time Difference Of Arrival Research Articles

Trajectories of astroparticles in pseudo-Finsler spacetime with the most general modified dispersion

Finsler geometry is a natural and fundamental generalization of Riemann geometry, and is a tool to research Lorentz invariance violation. We find the connection between the most general modified dispersion relation and a pseudo-Finsler structure, and then we calculate the arrival time delay of astroparticles with different modified dispersion relations in the framework of Finsler geometry. The result suggests that the time delay is irrelevant with the exact form of the modified dispersion relation. If the modified term becomes 0 when E=p, there is no arrival time difference, otherwise the time delays only depend on the Lorentz violation scale and the order at which the Lorentz invariance breaks.

Neighborhood Selection Synchronization Mechanism-Based Moving Source Localization Using UAV Swarm

To obtain the accurate time difference of arrival (TDOA) and frequency difference of arrival (FDOA) for passive localization in an unmanned aerial vehicle (UAV) swarm, UAV swarm network synchronization is necessary. However, most of the traditional distributed time synchronization protocols are based on iteration, which hinders efficiency improvement. High communication costs and long convergence times are often required in large-scale UAV swarm networks. This paper presents a neighborhood selection-all selection (NS-AS) synchronization mechanism-based moving source localization method for UAV swarms. First, the NS-AS synchronization mechanism is introduced, to model the UAV swarm network synchronization process. Specifically, the UAV neighbors are first grouped by sector, and the most representative neighbors are selected from each sector for the state update calculation. When the UAV swarm network reaches a fully connected state, the synchronization mechanism is switched to select all neighbors, to improve the convergence speed. Then, the TDOA-FDOA joint localization algorithm is employed to locate the moving radiation source. Through simulation, the effectiveness of the proposed method is verified by the system convergence and localization performance under different parameters. Experimental results show that the synchronization mechanism based on NS-AS effectively improves the convergence speed of the system while ensuring the accuracy of moving radiation source localization.

Variability in Early Surgery for Acute Cervical Spinal Cord Injury Patients: An Opportunity for Enhanced Care Delivery.

Data supporting the benefits of early surgical intervention in acute spinal cord injury (SCI) is growing. For early surgery to be accomplished, understanding the causes of variabilities that effect the timing of surgery is needed to achieve this goal. The purpose of this analysis is to determine factors that affect the timing of surgery for acute cervical SCI within the North American Clinical Trials Network (NACTN) for SCI registry. Patients in the NACTN SCI registry from 2005 to 2019 with a cervical SCI, excluding acute traumatic central cord syndrome, were analyzed for time elapsed from injury to arrival to the hospital, and time to surgery. Two categories were defined: 1) Early Arrival with Early Surgery (EAES) commenced within 24 h of injury, and 2) Early Arrival but Delayed Surgery (EADS), with surgery occurring between 24 to 72 h post-injury. Patients' demographic features, initial clinical evaluation, medical comorbidities, neurological status, surgical intervention, complications, and outcome data were correlated with respect to the two arrival groups. Of the 222 acute cervical SCI patients undergoing surgery, 163 (73.4%) were EAES, and 59 (26.6%) were EADS. There was no statistical difference in arrival time between the EAES and EADS groups. There was a statistical difference in the median arrival time to surgery between the EAES group (9 h) compared with the EADS group (31 h; p < 0.05). There was no statistical difference in race, sex, age, mechanism of injury, Acute Physiologic Assessment and Chronic Health Evaluation (APACHE) II scores, or medical comorbidities between the two groups, but the EAES group did present with a significantly lower systolic blood pressure (p < 0.05). EADS patients were more likely to present as an American Spinal Injury Association Impairment Scale (AIS) D than EAES (p < 0.05). Early surgery was statistically more likely to occur if the injury occurred over the weekend (p < 0.05). There were variations in the rates of early surgery between the eight NACTN sites within the study, ranging from 57 to 100%. Of the 114 patients with 6-month outcome data, there was no significant change between the two groups regarding AIS grade change and motor/pin prick/light touch score recovery. A trend towards improved motor scores with early surgery was not statistically significant (p = 0.21). Although there is data that surgery within 24 h of injury improves outcomes and can be performed safely, there remain variations in care outside of clinical trials. In the present study of cervical SCI, NACTN achieved its goal of early surgery in 73.4% of patients from 2005-2019 who arrived within 24 h of their injury. Variability in achieving this goal was related to severity of neurological injury, the day of the week, and the treating NACTN center. Evaluating variations within our network improves understanding of potential systemic limitations and our decision-making process to accomplish the goal of early surgery.

Evaluation of Station Timing Errors from Demeaned Arrival Time Delays

ABSTRACT We present an analytical solution for the evaluation of timing errors at seismological stations. The method makes use of differential P- and S-wave arrival time measurements demeaned over a network that recorded a set of densely located seismic events. In this configuration, one can assume coincident P and S ray paths between sources and receivers, and cancel out dependencies associated with absolute event origin times, event locations, and P- or S-wave velocities in the problem. Relative timing errors can be obtained by linear inversion, using only a limited amount of input data: differential P- and S-wave arrival times, and a local VP/VS ratio. By setting at least one reference station in the network, supposed to be devoid of any timing error, one can retrieve reliable timing errors for other stations. We validate the approach against synthetic and real data. We also analyze the sensitivity of results on errors in the input data. Although picking uncertainties do affect the variability of estimates, we also identified a significant bias when an incorrect VP/VS ratio is used. However, this bias can be reduced if one uses the optimal VP/VS value that minimizes the root mean square of travel-time residuals. Application of the method to a collection of manually picked arrival times for the 2002–2003 Tricastin, France, earthquake, swarm allowed us to identify nonstationary timing errors from tenth to tens of seconds during the monitoring campaign.

A Practice-Distributed Thunder-Localization System with Crowd-Sourced Smart IoT Devices.

Lightning localization is of great significance to weather forecasting, forest fire prevention, aviation, military, and other aspects. Traditional lightning localization requires the deployment of base stations and expensive measurement equipment. With the development of IoT technology and the continuous expansion of application scenarios, IoT devices can be interconnected through sensors and other technical means to ultimately achieve the goal of automatic intelligent computing. Therefore, this paper proposes a low-cost distributed thunder-localization system based on IoT smart devices, namely ThunderLoc. The main idea of ThunderLoc is to collect dual-microphone data from IoT smart devices, such as smartphones or smart speakers, through crowdsourcing, turning the localization problem into a search problem in Hamming space. We studied the dual microphones integrated with smartphones and used the sign of Time Difference Of Arrival (TDOA) as measurement information. Through a simple generalized cross-correlation method, the TDOA of thunderclaps on the same smartphone can be estimated. After quantifying the TDOA measurement from the smartphone node, thunder localization was performed by minimizing the Hamming distance between the binary sequence and the binary vector measured in a database. The ThunderLoc system was evaluated through extensive simulations and experiments (a testbed with 30 smartphone nodes). The extensive experimental results demonstrate that ThunderLoc outperforms the main existing schemes in terms of effectively locating position and good robustness.

Efficient Underwater Acoustical Localization Method Based on TDOA with Sensor Position Errors

Underwater acoustic localization (UWAL) is extremely challenging due to the multipath nature of extreme underwater environments, the sensor position uncertainty caused by unpredictable ocean currents, and the lack of underwater observation data due to sparse array, which all affect localization performance. Addressing these issues, this paper proposes a simple and effective underwater acoustic localization method using the time difference of arrival (TDOA) measurements based on the multipath channel effect of the underwater environment. By introducing the calibration source, localization performance was improved, and the sensor position error was corrected. The Cramér–Rao lower bound (CRLB) was derived, and the proposed method was able to achieve the CRLB with small deviation. Numerical simulations confirm the improved performance of the proposed method, including (1) a 20 dB and 30 dB reduction in the CRLB for far and near source scenarios, respectively, indicating improved accuracy and reliability when estimating unknown sources; (2) better Mean Squared Error (MSE) performance compared to existing methods and an efficiency of over 90% in low noise and above 80% in moderate noise in several scenarios, with a delayed threshold effect; and (3) achieving CRLB performance with only three sensors in a 3D space, even under moderate noise, while existing methods require at least five sensors for comparable performance. Our results demonstrate the efficacy of the proposed method in enhancing the accuracy and efficiency of source localization.

Target Positioning and Tracking in WSNs Based on AFSA

In wireless sensor networks (WSNs), the target positioning and tracking are very important topics. There are many different methods used in target positioning and tracking, for example, angle of arrival (AOA), time of arrival (TOA), time difference of arrival (TDOA), and received signal strength (RSS). This paper uses an artificial fish swarm algorithm (AFSA) and the received signal strength indicator (RSSI) channel model for indoor target positioning and tracking. The performance of eight different method combinations of fixed or adaptive steps, the region segmentation method (RSM), Hybrid Adaptive Vision of Prey (HAVP) method, and a Dynamic AF Selection (DAFS) method proposed in this paper for target positioning and tracking is investigated when the number of artificial fish is 100, 72, 52, 24, and 12. The simulation results show that using the proposed HAVP total average positioning error is reduced by 96.1%, and the positioning time is shortened by 26.4% for the target position. Adopting HAVP, RSM, and DAFS in target tracking, the positioning time can be greatly shortened by 42.47% without degrading the tracking success rate.

High-timing-precision detection of single X-ray photons by superconducting nanowires.

Precisely acquiring the timing information of individual X-ray photons is important in both fundamental research and practical applications. The timing precision of commonly used X-ray single-photon detectors remains in the range of one hundred picoseconds to microseconds. In this work, we report on high-timing-precision detection of single X-ray photons through the fast transition to the normal state from the superconductive state of superconducting nanowires. We successfully demonstrate a free-running X-ray single-photon detector with a timing resolution of 20.1ps made of 100-nm-thick niobium nitride film with an active area of 50μm by 50μm. By using a repeated differential timing measurement on two adjacent X-ray single-photon detectors, we demonstrate a precision of 0.87ps in the arrival-time difference of X-ray photon measurements. Therefore, our work significantly enhances the timing precision in X-ray photon counting, opening a new niche for ultrafast X-ray photonics and many associated applications.

Multi-TDOA Estimation and Source Direct Position Determination Based on Parallel Factor Analysis

In this paper, source localization exploiting time difference of arrival (TDOA) information is discussed, and a parallel factor (PARAFAC) analysis based method for multi-TDOA estimation and direct position determination (DPD) is proposed. Firstly, signals from the radiation source are received by multiple antennas through synchronous sensing. Then, the data from multiple antennas is fused by extracting the time delay matrix to construct a PARAFAC model. Thereafter, the time delay matrix is obtained by fast iterative decomposition using the trilinear alternating least square (TALS) algorithm. In the case of no multipath or weak multipath, where the typical scenario is the antennas being deployed on the airborne platform, the multi-TDOA estimation can be obtained simultaneously according to the time delay matrix to improve the processing speed. In the case of multipath, such as the antennas being located on the ground, the DPD cost function directly related to the source position can be established based on the time delay matrix, and the source position estimation can be achieved through grid search. Compared with other DPD methods, the proposed DPD method has better positioning performance and lower complexity. The effectiveness and superiority of the proposed methods are verified by both simulations and actual scenario tests.

A TDOA/AOA Hybrid Positioning Based on Improved Sparrow Search Algorithm for Mobile Position Estimation

To address the difficulty in calculating the nonlinear equation of time difference of arrival (TDOA) positioning, as well as the problem of measurement error in the hybrid time difference of arrival/angle of arrival (TDOA/AOA) positioning algorithm, an improved sparrow search algorithm is proposed to optimize positioning, and the optimization mechanism is retained on the basis of improving the performance of the original algorithm. The maximum likelihood estimation method is used to calculate the objective function, and then, the estimated function of the mobile station is used as the fitness function to generate the initial population of sparrows. Then, using particle swarm optimization, optimize the sparrow search algorithm and obtain the population’s optimal solution in order to obtain the optimal position. The simulation results show that, when compared to the existing algorithm, increasing the number of base stations increases the average accuracy of the sparrow search algorithm (SSA) positioning method by 18.54% and 4.5%, respectively, and, when compared to the proposed particle swarm optimization (PSO) positioning method, by 13.79% and 11.6% as the radius increases. The SSA hybrid positioning algorithm performs better in terms of positioning accuracy, convergence speed, and robustness.

Evaluation and revision of long-range single-site lightning location accuracy considering the time delay of ground wave

Detecting the distance and orientation of long-distance thunderstorms has very important practical significance. The multi-station lightning location system relies on a high-precision time module and good network communication capabilities, but in some cases these conditions cannot be met, but there is still a need for lightning activity monitoring, and it is very important to establish a single-site lightning location system. In this paper, we have established a long-distance single-site lightning location station, and in order to improve the accuracy of distance estimation, a numerical algorithm is used to obtain the relationship between the ground wave arrival time delay and the propagation distance, and it is used to revise the time difference between the peak value of the skywave and ground wave. Moreover, we used multi-station lightning location data to revise the site-error in magnetic direction finder method to improve the accuracy of the direction calculation. The results show that the effective detection range of the single-site we have been established is 200 km–2000 km, and the revised average direction deviation dropped from 12.3° to 8.6°. The verification results of thunderstorms within the effective detection range show that the relative error of single-site lightning location is 8.4%–18.6% after the revision.

Accuracy Assessment of the Positioning of a Swarm of Underwater Vehicles in Relation to Four Surface Vehicles Using the TDOA Method

This paper presents the results of research on the accuracy assessment of the positioning of a swarm of underwater vehicles based on hydroacoustic measurements made with respect to four surface vehicles under the time difference of arrival (TDOA) method. The assessment consisted of the estimation of accuracy parameters for determining the position of an underwater vehicle in relation to surface vehicles forming a so-called moving geometrical measurement structure (MGMS) in the following shapes: square, rectilinear, triangular, and three-pointed. This demonstrated that MGMS makes it possible to estimate the relative position of underwater vehicles in a swarm with an accuracy of 2.1 m (RMS) over an area of approx. 1000 m2 and approx. 3.0 m (RMS) over an area of approx. 1600 m2. The most favourable MGMS shapes include three-pointedwhile maximising the size of the positioning area, where the positioning accuracy should not exceed 3.0 m (RMS)—and rectilinear—while maximising the size of the positioning area, where the positioning accuracy should not exceed 10.0 m (RMS).

A bi-layer model for berth allocation problem based on proactive-reactive strategy

To reduce the impact of equipment failure, vessel arrival time delay and other unexpected factors, container terminal managers need to develop a more robust berth scheduling plan while considering the recovery costs. To deal with the berth allocation problem (BAP) with uncertain arrival time, a proactive-reactive hybrid strategy to deal with the impact of uncertainty is proposed. According to the characteristics of BAP and proactive-reactive strategy, a bi-layer programming model is constructed. A robust baseline plan with buffer time is generated in the first layer, and a recovered scheduling plan is generated in the second layer according to the actual arrival time. The decisions between the two layers of models affect each other. In addition, an Adaptive cross-entropy algorithm (ACEA) is designed to solve the first layer model. Different from the traditional cross-entropy algorithm (CEA), an adaptive search strategy is added to further search and optimize the neighborhood of the elite solutions. Furthermore, heuristic adjustment strategies (HAS) are designed to deal with the second layer. The computational results demonstrate that the bi-layer model proposed in this paper can better balance the baseline schedule cost and the recovered schedule cost. Numerical experiments are carried out to assess the effectiveness of the proposed model and the efficiency of the proposed algorithms.

Data-based localisation methods using simulated data with application to small-scale structures

Several methods to localise sources of vibrations have been established in the literature. A great amount of those methods are based on databases with features of known impact positions. Great effort needs to be put into highly expensive experiments that deliver those databases. In this paper, we propose several simulation techniques that may replace the expensive experiments for source localisation. The paper compares the localisation accuracy of simulated and experimental data for two different localisation approaches, the reference database method and neural networks. Both methods process signal arrival time differences from several positions on the structure. The methods are exemplarily applied to a complex small-scale structure from the automotive industry: The small dimensions of the brake disk hat and the inclusion of holes is a challenging task for the accuracy of the applied localisation techniques. Results show that simulated data can replace experimentally gained data well in case of the reference database method, whereas the neuronal networks approach should stick to experimentally gained data. The evaluations show that, despite the small dimension, the relative localisation accuracy is within accepted ranges of literature.

Detection and localization of Goliath grouper using their low-frequency pulse sounds

The goal of this paper is to implement and deploy an automated detector and localization model to locate underwater marine organisms using their low-frequency pulse sounds. This model is based on time difference of arrival (TDOA) and uses a two-stage approach, first, to identify the sound and, second, to localize it. In the first stage, an adaptive matched filter (MF) is designed and implemented to detect and determine the timing of the sound pulses recorded by the hydrophones. The adaptive MF measures the signal and noise levels to determine an adaptive threshold for the pulse detection. In the second stage, the detected sound pulses are fed to a TDOA localization algorithm to compute the locations of the sound source. Despite the uncertainties stemming from various factors that might cause errors in position estimates, it is shown that the errors in source locations are within the dimensions of the array. Further, our method was applied to the localization of Goliath grouper pulse-like calls from a six-hydrophone array. It was revealed that the intrinsic error of the model was about 2 m for an array spanned over 50 m. This method can be used to automatically process large amount of acoustic data and provide a precise description of small scale movements of marine organisms that produce low-frequency sound pulses.

Preventing Hostile TOA/TDOA Localization With AF Relay

This letter proposes a relay-assisted transmission scheme to protect the source location privacy (SLP) against hostile localization based on time of arrival (TOA) or time difference of arrival (TDOA) estimation. To avoid being located, the source first transmits with small power, and then the signal is amplified by the relay node. The adversary’s localization error bounds are derived, and the optimization problem to maximize the destination’s received signal-to-noise ratio (SNR) is solved. The numerical results depict the effectiveness of the proposed scheme by showing that it achieves the required SLP with an acceptable loss in communication performance.

GNSS Spoofer Localization for Vehicles Based on Doppler and Clock Drift Double Difference

Global navigation satellite systems (GNSS) have been widely used in our daily lives. Meanwhile, GNSS are facing a severe threat of spoofing attacks, which can mislead users by false position, velocity and time (PVT) solutions, resulting in serious consequences. Especially, with the development of vehicle navigation, autonomous driving and unmanned aerial vehicles (UAV), increasing spoofing attacks have emerged towards vehicles, where anti-spoofing techniques are desperately needed. Among these techniques, spoofer localization is a necessary step to fundamentally address the spoofing attacks. Most of the conventional spoofer localization methods are based on time of arrival (TOA) or time difference of arrival (TDOA). These methods require measurements observed by multiple receivers at the same time, where time synchronization is indispensable. However, it is hard to apply these methods to the existing vehicles equipped with independent commercial receivers. To cope with this problem, in this paper we develop a flexible method for vehicles to locate a stationary spoofer based on Doppler and clock drift double difference (DCDD). DCDD is calculated using Doppler measurements and clock drift solutions of one vehicular receiver and another reference receiver. Generally, Doppler frequency of GNSS signals changes slowly with time, which releases the restriction for high-precision time synchronization. DCDD represents the Doppler frequency caused by the vehicle motion, from which the spoofer position can be estimated. In addition, with the elimination of irrelevant components in Doppler measurements, DCDD minimizes the user complexity required for localization, where at least two receivers and one vehicle is needed. Utilizing DCDD, an iterative weighted least squares (WLS) algorithm is used to solve the spoofer position, and a closed-form initial value is given to improve the convergence rate. We evaluate the localization performance by the derived Cramér-Rao lower bound (CRLB) in the presence of vehicle position and velocity errors. Simulations and field vehicle experiments are conducted to verify the feasibility and effective of the proposed method. The experimental results show that with an average vehicle velocity of 8 m/s, the horizontal localization error can be less than 40 m and 20 m, using DCDD observations of 4 epochs and 8 epochs respectively.

Detection and Localization of Multiple Ships Using Acoustic Vector Sensors on Buoyancy Gliders: Practical Design Considerations and Experimental Verifications

Real-time detection of illegal activities in maritime areas, such as drug trafficking or illegal fishing, is a very challenging task. It generally requires important and expensive means (patrol planes, coastguard, or navy ships) to provide an efficient monitoring of large areas. As ships emit noise due to their propulsion (propeller and engines), passive acoustic monitoring can be an effective alternative to accomplish this task, at a reasonable cost. To be efficient, the detection process should be autonomous, run in real-time, and should transmit information within a short period. In this study, we demonstrate the potential of using gliders equipped with a tri-dimensional acoustic vector sensor (AVS) to run a survey mission in total autonomy. Based on the ability of the AVS to measure the direction of arrival of the incoming wave, we develop an embedded and real-time processing chain to detect ships and to cluster detections in a multiple-sources scenario. We also propose a receiver that runs in real time to measure the time difference of arrival (TDOA) if multipath propagation occurs. The sonar contacts are transmitted every 30 s to a command and control (C2) station using an acoustic modem, without interrupting the detection process. The C2 can process the sonar contacts with a tracker for target localization; the article also shows that it is possible to get a good estimate of the source distance by processing the TDOA from multipath propagation. The proposed methods are validated on data recorded during an at-sea experiment in shallow waters.

Broadband Geoacoustic Inversions for Seabed Characterization of the New England Mud Patch

Geoacoustic inversions using broadband acoustic data acquired during the Seabed Characterization Experiment 2017 conducted in the New England Mud Patch area in March 2017 are presented in this article. The primary goal of the data inversions is to estimate the compressional wave speed and density profiles of the sediment layers. Both linear perturbative and nonlinear Bayesian inversion methods are utilized. These two inversion methods share the same principle of solution schemes, i.e., to minimize the difference between the signal acquired (or derived quantities) at the receiver and the prediction by the optimized bottom model. The differences between the two approaches are in the type of data utilized for inversion and on the inversion procedure used to determine the bottom geoacoustic properties. The linear inversion method uses the time difference of modal arrival, while the Bayesian inversion uses the bandpass-filtered sound pressure waveform. One of the study objectives is for the Bayesian inversion to provide a reference solution to the inverse problem and determine the ability of the linear inversion method to provide comparable results as compared with a more exhaustive search used in the Bayesian method. Another objective is to use the verified linear inversion method that is computationally faster to explore different models of sediment layering structure and to estimate the most appropriate bottom model for the experimental area.

Direct Position Determination Using Compressive Sensing Measurements Without Reconstruction

This paper proposes a direct position determination (DPD) method for stationary emitters with compressed signal measurements. Employing Hadamard matrix properties, the method estimates the source location directly in the compressing measurement domain, without the step of signal reconstruction and time-differences-of-arrival (TDOA) parameter extraction. In case of free space propagation, an augmented DPD method is proposed to further utilize the position related received signal strength (RSS) information. In addition, the Cram&#x00E9;r-Rao lower bounds (CRLBs) for emitter position of both DPD methods are derived for performance evaluation.