Time Difference Of Arrival Method Research Articles

Combined BDS/5G seamless positioning scheme based on joint switching strategy of satellite elevation angle and CNR in complex urban environments

Abstract Satellite-based positioning has gained popularity, but in bustling urban areas, signals face challenges like serious attenuation, affecting the reliability of positioning. To overcome this, we propose a seamless positioning approach that combines the BeiDou navigation satellite system (BDS) and 5G, specifically designed for complex urban settings. Initially, we establish static and dynamic positioning solutions using real 5G data measured through the time difference of arrival method, resulting in accurate 5G indoor positioning. Following this, we develop a combined BDS/5G positioning model incorporating joint switching based on satellite elevation angle and carrier-to-noise ratio (CNR). We conduct positioning experiments in intricate environments to validate the effectiveness of our model. The experimental outcomes demonstrate that our combined BDS/5G seamless positioning model, employing the joint switching strategy of satellite elevation angle and CNR, achieves impressive positioning accuracies ranging from decimeters to meters. This approach markedly enhances accuracy and reliability of seamless positioning in challenging urban scenarios.

SFDM: A time-synchronization-free detection mechanism for mobile underwater acoustic sensor networks

Detection and localization are important applications of underwater acoustic sensor networks, and the use of passive listening arrays composed of multiple underwater unmanned platforms to achieve passive detection and localization of targets has been a hot research topic in recent years. However, most schemes based on mobile listening arrays only aim to improve localization accuracy, with less consideration of the high communication and time overhead of formation maintenance and the high cost of time synchronization among nodes. To reduce the cost while ensuring localization accuracy, this paper proposes a time-synchronization-free detection mechanism for mobile underwater acoustic sensor arrays. Initially, the nodes cruise underwater until they passively detect a target signal. Subsequently, a pseudo-synchronization and rough self-calibration process is triggered among the nodes, which relies on the communication among the nodes. The communication stage is based on a time-synchronization-free detection protocol. An improved sound speed stratification effect compensation algorithm and an unscented particle filter algorithm are proposed to improve the calibration accuracy of the array. Finally, the Time Difference of Arrival method is utilized to locate the target position. Simulation and sea trial results confirm the feasibility and accuracy of the proposed mechanism. In addition, the mechanism is effective in reducing hardware costs.

Collaborative positioning for emergency rescuers based on INS, GPS and ZigBee

Multi-person cooperative positioning is one of the main techniques to improve the success rate of search and rescue. Nevertheless, current integrated positioning solutions for ZigBee and inertial navigation system (INS) are insufficiently versatile and commonly necessitate pre-existing infrastructure within the area. In this study, it is not necessary to install ZigBee positioning anchors in the environment in advance, and all positioning devices were mounted on rescuers, in contrast to previous positioning methods. First, an improved time difference of arrival (TDOA) method is proposed, which weights the position coordinates to minimize positioning errors. Then, the position data of the commander and the rescuers are substituted into the hyperbolic equations of the improved TDOA method, and the initial position of the rescuers is solved by Taylor method. Finally, based on the initial position, an improved Extended Kalman filter (EKF) position update technology is proposed, which uses ZigBee positioning system to monitor the east and north position of rescuers, and uses barometers to measure the altitude of rescuers. The magnetometers are used to limit the heading angle of the rescuers, so as to realize the high-precision 3D positioning of the emergency rescuers in the harsh environment. In this paper, three different scenarios are used to verify the effectiveness of the proposed method. The experimental results demonstrate that, when compared to the inertial positioning method, the traditional TDOA method, and the cooperative positioning method based on the relative ranging constraints of UWB and INS, respectively, the average positioning accuracy of the proposed method is 68.58%, 48.71%, and 13.59% higher.

Data-Driven Inline Leak Detection for Pipelines Using Flow-Induced Acoustics Analysis

Fluid and water distribution networks are essential to the modern world. However, these systems are prone to leaks, which can lead to significant water loss, damage to infrastructure, and environmental pollution. The proposed solution makes use of Acoustic Emission sensors placed in discrete locations in the pipeline which measures the sound in the pipeline caused by the flow of fluids. Computation models are used to deduce the location from the input provided by the sensors. In case of leak, the leak is localized through cross correlation and TDOA methods. This solution is particularly developed for water distribution pipelines. Keyword: Acoustic data analysis, Data-driven models, Cross-Correlation, Time Difference of Arrival (TDOA)

Acoustic emission source location for composite tubes using finite element simulation and machine learning

ABSTRACT Acoustic emission is widely used in engineering structural health monitoring, where damage location based on acoustic emission have great advantages. Currently, most of the acoustic emission location work requires extensive experimental studies. In this study, acoustic emission source location model was proposed based on BP neural network and acoustic emission wave propagation simulation, thus reduced the experiments required for acoustic emission localisation and improved the location accuracy. Initially, finite element simulation was conducted to study the propagation of acoustic emission waves in composite tubes. The calculated findings showed a high level of agreement with the experimental data. Additionally, the first arrival time of the signal was extracted according to the Akaike information criterion, and the neural network was trained and tested using the simulated data, while the trained network model was validated using the experimental data. The results show that the finite element method is a reliable alternative test method. More than 94% of the sound source location results have absolute location error within ± 3 mm, and the all points is less than ± 5 mm. The deviation of the location results showed significant improvement compared to the traditional time difference of arrival method, verifying the feasibility of the method.

Comparison of two options for building three-coordinate electronic intelligence stations

The subject–coordinate measurement methods in ground electronic intelligence (ELINT) stations. The goal is to conduct a comparative analysis of two options for the composition ground ELINT stations in terms of accuracy of measuring coordinate information. The tasks to be solved are as follows: assessing the accuracy of determining the coordinates of the time difference of arrival method (TDOAМ) and hybrid method (HM); obtaining analytical ratios for estimating the root-mean-square error (RMSE) of the accuracy of measuring the altitude of radio emission sources (RES) of these methods; on the basis of the obtained estimates and analytical ratios, a comparative analysis of the methods, under conditions where the accuracy of the coordinate information obtained by both methods is commensurate; and development of recommendations regarding the practical application of HM coordinate measurements. The methods used are: the theory of measurements and the theory of evaluation of coordinate information. The following results were obtained: a comparative analysis of the TDOAМ and HM was performed according to the RMSE of the determination of plane coordinates and the altitude of the RES. The accuracy assessment was performed in a known way, based on the linearization of the functional dependence between the measured primary parameters (range differences, elevation angle) and spatial coordinates by expanding in a Taylor series with the deduction of the first two terms of the series. Calculations have shown that the presence of the third side station has very little effect on the accuracy of determining plane coordinates. Significant differences appear only in the results of estimating the RMSE of the RES altitude. To compare the methods, analytical relationships were obtained for estimating the RMSE of the altitude measurement. The condition is determined under which the accuracy of determining the altitude for the HM is not worse than that for the TDOAМ (the accuracy is the same). Starting from this value and further, when using the HM, the altitude is determined more accurately. Conclusions. An HM of high-precision determination of 3 coordinates in ELINT stations, based on measuring two distance differences and direction finding (DF) in the elevation plane, can, with a smaller number of side stations (two instead of three), provide accuracy no worse than the known TDOAM. However, this requires that the RMSE value for DF in elevation should be tenths of degrees. The practical application of HM is possible for the issuance of target designations on air defense missile systems radar.

Gas-insulated switchgear partial discharge acoustic–electric joint localisation method based on the Salp Swarm Algorithm and least squares estimation

Partial discharge (PD) is an early warning of gas-insulated switchgear (GIS) insulation faults. Consequently, accurate localisation of PD is crucial for the safe operation of GIS. The time difference of arrival method based on acoustic emission technology is more favorable for the engineering application of PD source localisation owing to its noninvasive characteristics and the small amount of required data. However, because PD ultrasonic signal propagation in GIS will introduce a variety of errors, current localisation algorithms suffer from problems of low accuracy and poor stability. Therefore, this study simulate and analyse the ultrasonic propagation characteristics as well as the sources of errors in GIS, based on which a joint acoustic–electric localisation method based on the Salp Swarm Algorithm is proposed, and an error-correction method based on least squares estimation is introduced. The localisation results show that the proposed method can effectively reduce the localisation error caused by multiple sources of error, and the mean localisation error can be reduced to within 20 mm in different structural gas chambers of GIS, which is more accurate and more stable compared with other methods, and it has good value for engineering application.

Localizing multiple sound sources using an array of autonomous, asynchronous receivers

Time-difference-of arrival (TDOA) methods are well established and commonly used to localize sound sources in bioacoustic applications. TDOA methods generally require/assume that the receivers of the acoustic array are time-synchronized. Time synchronization can be achieved in various ways, including by connecting the receivers to a common data aquisition device, or by using control/calibration sources of known location to time synchronize. In this talk, we introduce a TDOA approach that can be used with an array of autonomous, asynchronous receivers. The approach requires that multiple sources are detected over the array, and localizes the sources simultaneously in addition to solving for clock offsets between the receivers. This approach offers potential cost and time savings since it can be used with autonomous receivers and since it does not require control/calibrationsources. Simulation results will be used to illustrate and explore the approach, and results from an experiment using asynchronous microphones will be presented. [Work supported in part by ONR.]

An Efficient Hybrid Multi-Station TDOA and Single-Station AOA Localization Method

Multi-station passive localization algorithms based on hybrid Time Difference of Arrival (TDOA) and Angle of Arrival (AOA) have been thoroughly studied. But it usually requires each station to obtain the AOA of the source and relies on the precise station position. These conditions are generally not satisfied in practical applications. In addition, the geometry between the source and these stations also affects the localization accuracy. This paper studies the passive source localization problem based on multi-station TDOA and single-station AOA measurements. First, we propose a closed-form solution source localization method based on multi-station TDOA and single-station AOA measurements, which requires only the reference station used to calculate TDOA to be able to observe the AOA measurements of the source. It solves the problem of hybrid localization of different numbers of TDOA and AOA measurements. Theoretical analysis proves that the performance of the proposed method can reach the Cramer-Rao Lower Bound (CRLB) under small noise conditions. Then, we model the relationship between the position of each station relative to the source and the localization accuracy. Through the D-optimality criterion, we obtain the optimal geometry between multiple stations and the source Simulation results confirm the validity of these theories.

Design and Performance Analysis of Sound Source Localization using Time Difference of Arrival Estimation

Sound source localization (SSL) is a process of processing sound signals received from sound sensors and locating the sound origin. In many applications, precise localization of these sound sources is crucial. The accuracy of the localization of the sound source depends on several factors, and one of the factors is the number of sound sensors. This work aims to develop a microcontroller-based sound sensor localization system using the Time Difference of Arrival (TDOA) method, as well as to analyze SSL by comparing the time difference received by two and three sound sensors with respect to the distance of sound, and to compare the angle accuracy of the sound localization through TDOA with the real sound location. A few experimental tests were conducted using a constant sound of 90db and a frequency range of sound of 50Hz to 10kHz. The mean error (inaccuracy) of the experimental test of the angle acquired within 5cm of the source is 34.66°, while the angle obtained within 10cm of the source is 34.29°. The difference in angle inaccuracy between two and three sensors has a reduction of 27.64%. By adding more sound sensors, angle accuracy can be increased through the TDOA method.

Robust localization under NLOS environment in the presence of isolated outliers by full-Set TDOA measurements

Different from the traditional approach of using the reduced set of time-difference-of-arrival (TDOA) measurements, localization by the full TDOA set is discussed here. It avoids choosing a specific reference sensor and exploits more measurements, conferring robustness against outliers. Nevertheless, the none-line-of-sight (NLOS) propagation still presents challenges for the existing full-set positioning algorithms. In this work, we develop an iterative scheme that utilizes the full TDOA measurements for localization capable of simultaneously mitigating the influence of outliers and NLOS-path measurements. The proposed scheme consists of the localization and identification modules, and they are designed with low complexity to meet real-time positioning demands. The theoretical optimal TDOA methods using full-set measurements are proposed in the localization module. Besides, to identify the NLOS measurements, the identification module adopts a greedy search-based random sample consensus (GS-RSC) algorithm. It can work cooperatively with the proposed lightweight localization module, returning a set free of outliers, NLOS measurements, and an accurate source location estimate. The theoretical analysis and experiments illustrate the superiority of the proposed scheme over the state-of-the-art TDOA full-set algorithms for handling outliers and NLOS measurements in localization.

Application of Classified Elastic Waves for AE Source Localization Based on Self-Organizing Map

Acoustic emission (AE) source localization has been used to visualize progress failures generated in a wide variety of materials. In the conventional approaches, AE source localization algorithms assume that the AE signal is propagated as a straight line. However, it is supposed that progress failures form heterogeneity of elastic wave velocity distributions. Hence, with the conventional source localization, it is expected that the localization accuracy is reduced in heterogeneous materials since diffraction and refraction waves are generated. Thus, if the straight propagation waves are classified, conventional source localizations are performed in the heterogeneous materials. The self-organizing map (SOM) is one of the unsupervised learning methods, and the SOM has potential to classify straight propagation waves for the source localizations. However, the application of classified AE signals in source localization is not popular. If classified AE signals are applied to the time difference of arrival (TDOA) method, which is the popular localization method, it is expected that number of visualized sources are decreased because the algorithm does not consider the selection of the propagated wave. Although ray tracing has potential to localize a larger number of sources than the TDOA method, it is expected that the localized sources are less accurate in comparison with results of the TDOA method. In this study, classified waves were applied to two of the source localizations, and model tests based on pencil-lead breaks (PLBs) generating artificial AE sources were conducted to validate the performance of the source localizations with classified waves. The results of the validation confirmed that the maximum error in the TDOA method is larger in comparison with ray tracing conducted with 20 mm intervals of source candidates. Moreover, ray tracing localizes the same number of sources as the number of PLB tests. Therefore, ray tracing is expected to more practically localize AE sources than the TDOA method if classified waves are applied.

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).

Improving TDOA Radar Performance in Jammed Areas through Neural Network-Based Signal Processing

This paper presents a method for estimating the position of a target under jammed conditions using the Time Difference of Arrival (TDOA) method. The algorithm utilizes a deep neural network to overcome the challenges posed by the jammed conditions. The simulations and results indicate that the presented method is more accurate and efficient than the traditional TDOA methods.

Array invariant-based range-only target motion analysis for ship noise measured by two vertical line arrays in shallow water

A novel approach for underwater acoustic localization by using passive line array sonar will be proposed in this talk. In the case of the received signal having a finite pulse duration, the target location can be easily estimated using the time-difference-of-arrival (TDOA) method between sensors. However, it is difficult to use the TDOA method for signals that exist for a relatively long time, such as ship noise. An array invariant method has been proposed to measure the source-receiver distance, but it does not accurately estimate the target location. In this talk, target localization will be performed with the range-only target motion analysis method using non-linear target tracking after estimating the target range by the array invariant method. The proposed method is tested using the ship noise of the R/V Onnuri measured by two vertical line arrays during the Shallow-water Acoustic Variability Experiment (SAVEX-15), and the result will be discussed in this talk. [This research was supported by the Ministry of Oceans and Fisheries of Korea (PM63010, 2022).]

Joint TDOA, FDOA and PDOA Localization Approaches and Performance Analysis

Multi-station joint localization has important practical significance. In this paper, phase difference of arrival (PDOA) information is introduced into the joint time difference of arrival (TDOA) and frequency difference of arrival (FDOA) localization method to improve the target localization accuracy. First, the Cramer–Rao lower bound (CRLB) of the joint TDOA, FDOA and PDOA localization approach with multi-station precise phase synchronization is derived. Then, the CRLB of the joint TDOA, FDOA and differential PDOA (dPDOA) localization method for the case of phase asynchronization between observation stations is also presented. Furthermore, the authors analyze the influence of the phase wrapping problem on localization accuracy and propose solutions to solve the phase wrapping problem based on cost functions of grid search. Finally, iterative localization algorithms based on maximum likelihood (ML) are proposed for both TDOA/FDOA/PDOA and TDOA/FDOA/dPDOA scenarios, respectively. Simulation results demonstrate the localization performance of the proposed approaches.

An Improved TDOA Method for Land-Based Long-Range HF Skywave Source Geolocation and Experimental Results

The real-time information of the unknown ionospheric environments is difficult to obtain, plaguing the timely and accurate geolocation of high frequency (HF) sources. In this paper, we propose an improved HF skywave source geolocation method based on the time-difference-of-arrival (TDOA) with the semidefinite programming (SDP), and model HF signal propagation paths as paths with significant non-line-of-sight (NLOS) biases. With this method, no priori information about the ionosphere, especially the priori ionospheric virtual heights of reflection, is necessary while timely and accurately geolocating the HF sources. Furthermore, we use the ray tracing technique and build a 3D ionospheric electron density gridded matrix model to simulate realistic HF signal propagation paths. In the simulations, the proposed method is compared with existing methods, and detailed geolocation error distribution maps are given. In the experiments, HF I/Q data captured from different types of HF transmitters are located by six receivers with time synchronization. Simulated and experimental results show that the proposed method improves the positioning accuracy by about 50% compared with existing methods under the same conditions, and the average relative positioning error is less than 2.7%.

ИСПОЛЬЗОВАНИЕ МЕТОДА TDOA ДЛЯ ПОДТВЕРЖДЕНИЯ ДОСТОВЕРНОСТИ ИНФОРМАЦИИ РАДИОВЕЩАТЕЛЬНОГО АВТОМАТИЧЕСКОГО ЗАВИСИМОГО НАБЛЮДЕНИЯ

The paper considers the possibility of using the Time Difference of Arrival (TDOA) method, which can be applied to confirm the reliability of information coming from multiple sources. TDOA method can be applied to validate the information received from several ground automatic dependent surveillance stations of broadcast type (ADS-B). The paper is aimed at studying the TDOA method and its application to ADS-B stations. This method makes it possible to use the ADS-B as the only means of surveillance at the airfield. Currently, according to ICAO recommendations, ADS-B stations are not allowed to be used as a stand-alone surveillance aid due to the problems related to the possibility of distorting a signal or introducing some false information into messages, so the operation of this type of stations is possible only together with other means of surveillance, such as multi-position surveillance systems (MLAT) or secondary surveillance radar systems (SSR) thus increasing the cost of organizing surveillance on the airfield. Thus, the relevance of the work is related to the need to find an alternative method of confirming the validity of an ADS-B message.

Concurrent Bidirectional TDoA Positioning in UWB Network With Free-Running Clocks

This article proposes an approach of time-difference-of-arrival (TDoA) positioning in ultrawideband networks, where user tags localize themselves by means of the exploitation of the broadcasted synchronization messages of the anchor network. Such an approach promises an unlimited number of localized devices; moreover, the position is available directly at the user terminal. The key challenge of this method is to eliminate the errors caused by tag clock drifts, which render the TDoA measurements useless when left uncorrected. Our method employs extended Kalman filtering for the estimation of position and the elimination of the drift-induced errors. It is shown that the system performance is similar to that of the more common TDoA method, where the tags transmit blinks received by the anchors. However, the anchors are still able to receive the blink messages and estimate the position of those tags, since the synchronization messages are exploited. Therefore, it is possible to use both the directions of TDoA positioning concurrently; a limited number of tags is tracked by the infrastructure and all tags may compute their positions. The TDoA solutions have achieved a root-mean-square horizontal accuracy of 25.9 and 33.6 cm, respectively.

Fast TDOA and FDOA Estimation for Coherent Pulse Signals

Time difference of arrival (TDOA) and frequency difference of arrival (FDOA) have been widely used for localizing temporally continuous signals passively. Temporal sparsity of pulse signals makes their TDOA and FDOA estimation processes much different, and computational complexity is a major concern in this area. This paper addresses the problem of fast TDOA and FDOA estimation of pulse signals and focuses mainly on narrowband coherent pulses. By decoupling the effects of TDOA and FDOA in the cost function of localization approximately, we propose a fast coarse TDOA and FDOA estimation method. The estimates are then refined with the cross-ambiguity function (CAF) algorithm within a small TDOA and FDOA neighborhood. In the simulations, the proposed method is demonstrated to have satisfying TDOA and FDOA estimation precisions, and it exceeds existing counterparts largely in computational efficiency.