Bibliografie tematiche / TDOA

Letteratura scientifica selezionata sul tema "TDOA"

Autore: Grafiati
Pubblicato: 4 giugno 2021
Ultima modifica: 25 maggio 2024

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Articoli di riviste sul tema "TDOA"

1

Chen, Xiang, Yuheng Chen, Shuai Cao, Lei Zhang, Xu Zhang e Xun Chen. "Acoustic Indoor Localization System Integrating TDMA+FDMA Transmission Scheme and Positioning Correction Technique". Sensors 19, n. 10 (22 maggio 2019): 2353. http://dx.doi.org/10.3390/s19102353.

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This paper presents a novel audio indoor localization system. In the proposed system, four speakers placed at known positions transmit chirp signals according to the time-division multiple access (TDMA) plus frequency-division multiple access (FDMA) transmission scheme. A smartphone receives the signal via a built-in microphone and calculates the time differences of arrival (TDOAs). Using TDOA measurements, the position is estimated by the shrinking-circle method. In particular, to reduce the positioning error in moving conditions, a TDOA correction method based on Doppler shifts is proposed. The performance of the proposed system was evaluated in real-world experiments using a 10.971 m × 5.684 m positioning area. The results of the static-target positioning experiment showed that the TDMA+FDMA transmission scheme has more advantages in improving the update rate of the positioning system than the TDMA-only transmission scheme. The results of the moving-target positioning experiment under three different speeds demonstrated that the positioning errors were reduced by about 10 cm when the Doppler-shift-based TDOA correction method was adopted. This research provides a possible framework for the realization of a TDOA-chirp-based acoustic indoor positioning system with high positioning accuracy and update rate.
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2

Luo, Ji-An, Zhi-Wen Tan e Dong-Liang Peng. "A novel bearing-assisted TDOA-GROA approach for passive source localization". International Journal of Intelligent Computing and Cybernetics 11, n. 1 (12 marzo 2018): 2–19. http://dx.doi.org/10.1108/ijicc-11-2016-0056.

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Purpose The passive source localization (PSL) problem using angles of arrival (AOA), time differences of arrival (TDOA) or gain ratios of arrival (GROA) is generally nonlinear and nontrival. In this research, the purpose of this paper is to design an accurate hybrid source localization approach to solve the PSL problem. The inspiration is drawn from the fact that the bearings, TDOAs and GROAs are complementary in terms of their geometry properties. Design/methodology/approach The maximum-likelihood (ML) method is reexamined by using hybrid measurements. Being assisted by the bearings, a new hybrid weighted least-squares (WLS) method is then proposed by jointly utilizing the bearing, TDOA and GROA measurements. Findings Theoretical performance analysis illustrates that the mean-square error of the ML or WLS method can attain the Cramér-Rao lower bound for Gaussian noise over small error region. However, the WLS method has much lower computational complexity than the ML algorithm. Compared with the AOA-only, TDOA-only, AOA-TDOA, TDOA-GROA methods, the localization accuracy can be greatly improved by combining the AOAs, TDOAs and GROAs, especially for some specific geometries. Originality/value A novel bearing-assisted TDOA-GROA method is proposed for source localization, and a new hybrid WLS estimator is presented inspired from the fact that the bearings, TDOAs and GROAs are complementary in terms of their geometry properties.
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Ouyang, Xinxin, Shanfeng Yao e Qun Wan. "A Coherent Integrated TDOA Estimation Method for Target and Reference Signals". Electronics 11, n. 16 (22 agosto 2022): 2632. http://dx.doi.org/10.3390/electronics11162632.

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Abstract (sommario):
The performance of a time difference of arrival (TDOA) localization system is severely affected by time synchronization errors, and making use of reference signals is a common solution for the problem. The traditional method has two steps, first to measure the TDOAs of the target signal and reference signal separately, and next, to compensate the estimated target TDOA with the difference of the estimated reference TDOA and the true reference TDOA. Since the performance of the TDOA estimation is mainly decided by the frequency information, a coherent integration TDOA estimation method for the target signal and reference signal is proposed in this paper, based on cross correlation phase difference compensation, with use of the signals’ frequencies. First, as per the traditional method, the separated cross correlation functions of the target signal and reference signal were obtained by cross correlation, and the target TDOA and reference TDOA of the separate method were estimated. Next, the cross correlation phase was analyzed for each signal. Then the coherent integration cross correlation was obtained with phase compensation, from which the estimation of the target TDOA and reference TDOA could simultaneously be achieved. We performed simulation comparisons with the two methods, and showed that the proposed algorithm provided better performance.
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4

Wada, Atsushi, e Shingo Yoshizawa. "Transmission of Depth Data by Pulse Position Modulation for Underwater Acoustic Positioning Systems". International Journal of Circuits, Systems and Signal Processing 16 (30 maggio 2022): 999–1006. http://dx.doi.org/10.46300/9106.2022.16.122.

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This paper presents a three dimensional localization method for underwater acoustic positioning systems. In typical ultra-short baseline (USBL) acoustic positioning systems, the three dimensional position is localized by using multiple time difference of arrivals (TDOAs). Since the TDOA accuracy is less than the other sensor data, we focus on a localization method with the minimum number of TDOA. We propose a method of transmitting depth data by pulse position modulation (PPM), where the target position is localized by a single TDOA, a distance, and a depth. The proposed method shows a higher positional accuracy than the conventional method with two TDOAs. The effectiveness of the proposed method has been demonstrated in the evaluation of simulation and experiment.
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Deng, Wang, Zheng, Fu, Yin, Tang e Yang. "A Closed-Form Localization Algorithm and GDOP Analysis for Multiple TDOAs and Single TOA Based Hybrid Positioning". Applied Sciences 9, n. 22 (16 novembre 2019): 4935. http://dx.doi.org/10.3390/app9224935.

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Cellular communication systems support mobile phones positioning function for Enhanced-911 (E-911) location requirements, but the positioning accuracy is poor. The fifth-generation (5G) cellular communication system can use indoor distribution systems to provide accurate multiple time-difference-of-arrival (TDOA) and single time-of-arrival (TOA) measurements, which could significantly improve the indoor positioning ability. Unlike iterative localization algorithms for TDOA or TOA, the existing closed-form algorithms, such as the Chan-Ho algorithm, do not have convergence problems, but can only estimate position based on one kind of measurement. This paper proposes a closed-form localization algorithm for multiple TDOAs and single TOA measurements. The proposed algorithm estimates the final position result using three-step weighted least squares (WLSs). The first WLS provides an initial position for the last two steps. Then the algorithm uses two WLSs to estimate position based on heteroscedastic TDOA and TOA measurements. In addition, the geometric dilution of precision (GDOP) of the proposed hybrid TDOA and TOA positioning has been derived. The analysis of GDOP shows that the proposed hybrid positioning has lower GDOP than TDOA-only positioning, which means the proposed hybrid positioning has a higher accuracy limitation than TDOA-only positioning. The simulation shows that the proposed localization algorithm could have better performance than closed-form TDOA-only positioning methods, and the positioning accuracy could approximate Cramer-Rao lower bound (CRLB) when the TDOA measurement errors are small.
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6

IBRAHIM, NUR. "Pendeteksian Lokasi Sumber Noise (Partial Discharge) secara Tiga Dimensi menggunakan Antenna Array". ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika 3, n. 2 (1 luglio 2015): 106. http://dx.doi.org/10.26760/elkomika.v3i2.106.

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ABSTRAKPada penelitian ini akan dilakukan simulasi teknik pendeteksian lokasi sumber noise berupa partial discharge (PD) pada peralatan tegangan tinggi, dengan menggunakan susunan antena yang terdiri dari empat buah antena monopole sebagai sensor untuk mendeteksi gelombang elektromagnetik (EM) yang dipancarkan dari partial discharge (PD). Algoritma yang digunakan mengacu kepada time difference of arrival (TDOA) dari sinyal yang diterima antar antena (dengan menjadikan salah satu antena sebagai antena referensi). Metode yang digunakan untuk menentukan TDOA adalah metode Akaike Information Criterion, metode Energy Criterion, metode Gabor Centroid, metode threshold detection, metode peak detection, dan metode cross-correlation. Sistem pendeteksian lokasi sumber noise ini menggunakan konfigurasi susunan antena membentuk Y. Jarak antar antena diatur sejauh 2 meter dan 4 meter. Berdasarkan hasil pengamatan dan analisis, konfigurasi susunan antena membentuk Y memiliki tingkat akurasi 97.67%. Metode yang paling akurat untuk menentukan TDOA adalah metode cross-correlation.Kata kunci: PD, TDOA, susunan antena.ABSTRACTThis paper presents a simulation of locating noise source (Partial Discharge) on high-voltage apparatuses, by using antenna array that consisted of four monopole antennas as sensor to record the electromagnetic waves (EM) emitted from Partial Discharge (PD). The detection algorithm is based on the time difference of arrival (TDOA) of the signals received between antennas (by using one of four antennas as reference antenna). The methods to determine TDOAs are Akaike Information Criterion method, Energy Criterion method, Gabor Centroid method, threshold detection method, peak detection method, and/or cross-correlation method. These system use Y-shaped array configuration. The adjusted distance between antennas are 2 meter and 4 meter. From the observation and analysis results, Y-shaped array antenna configuration has accuracy 97.76%. The best method to get TDOA is the cross-correlation method.Keywords: PD, TDOA, antenna array.
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7

Yuk, Simun, e Youngho Cho. "A Time-Based Dynamic Operation Model for Webpage Steganography Methods". Electronics 9, n. 12 (10 dicembre 2020): 2113. http://dx.doi.org/10.3390/electronics9122113.

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The webpage steganography technique has been used for a covert communication method for various purposes in which a sender embeds a secret message into a plain webpage file like an HTML file by using various steganography methods. With human eyes, it is very difficult to distinguish between the original webpage (cover webpage) and the modified webpage with the secret data (stego webpage) because both are displayed alike in a web browser. In this approach, when two communicating entities want to share a secret message, a sender uploads a stego webpage to a web server or modifies an existing webpage in the web server by using a webpage steganography method, and then a receiver accesses the stego webpage to download and extract the embedded secret data from it. Meanwhile, according to our extensive survey, we observed that most webpage steganography methods focused on proposing or improving steganography algorithms but did not well address how to operate a stego webpage as time passes. However, if a stego webpage is used in a static way such that the stego webpage does not change and is constantly exposed to web clients until the sender removes it, such a static operation approach will limit or badly affect the hiding capacity and undetectability of a webpage steganography method. By this motivation, in this paper, we proposed a time-based dynamic operation model (TDOM) that improves the performance of existing webpage steganography methods in terms of hiding capacity and undetectability by dynamically replacing the stego webpage with other stego webpages or the original webpage. In addition, we designed two time-based dynamic operation algorithms (TDOA-C and TDOA-U), which improve the hiding capacity of existing methods and TDOA-U for improving the undetectability of existing methods, respectively. To validate our model and show the performance of our proposed algorithms, we conducted extensive comparative experiments and numerical analysis by implementing two webpage steganography methods with our TDOM (CCL with TDOA-C and COA with TDOA-C) and tested them in the web environment. According to our experiments and analysis, our proposed algorithms could significantly improve the hiding capacity and undetectability of two existing webpage steganography methods.
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Liu, Yan, e Fucheng Guo. "Fast TDOA and FDOA Estimation for Coherent Pulse Signals". International Journal of Antennas and Propagation 2022 (20 settembre 2022): 1–9. http://dx.doi.org/10.1155/2022/5390970.

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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.
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Permana, Andriyan, Agfianto Eko Putra e Catur Atmaji. "Analisis Perkiraan TDOA menggunakan Algoritma LMS Adaptif pada Pelacakan Paus Lodan". IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) 5, n. 1 (1 maggio 2015): 11. http://dx.doi.org/10.22146/ijeis.7149.

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AbstrakPenelitian mengenai perkiraan TDOA dalam pelacakan paus lodan telah dilakukan[1] yang menggunakan Teager-Kaiser operator dalam peningkatan akurasi perkiraan nilai TDOA untuk pelacakan paus lodan menggunakan algoritma LMS adaptif. Namun demikian, belum dilakukan penelitian lebih lanjut mengenai faktor konvergensi (μ) yang tepat (cepat dan akurat) pada perkiraan TDOA menggunakan algoritma LMS adaptif untuk pelacakan paus lodan. Akan dilakukan analisis perkiraan nilai TDOA menggunakan algoritma LMS adaptif pada pelacakan posisi paus lodan dengan variasi nilai μ. Pada penelitian ini, sebagai acuan untuk menentukan nilai μ yang tepat, digunakan hasil pelacakan paus pada penelitian [2].Perkiraan TDOA menggunakan algoritma LMS Adaptif pertama kali dipublikasikan oleh Benesty [3]. Pendekatan yang dilakukan berdasarkan pada perkiraan tanggap impulsional dari sumber ke penerima. Pada algoritma LMS adaptif dilakukan pembaruan nilai koefisien dengan μ sebagai langkah adaptasi. Nilai TDOA diperoleh dari selisih jarak dua tanggap impulsional.Dari hasil penelitian diperoleh hasil bahwa perubahan nilai μ mempengaruhi kecepatan perkiraan TDOA menggunakan algoritma LMS adaptif. Akan tetapi, nilai μ yang tidak tepat mengakibatkan hasil pelacakan paus tidak akurat. Dari penelitian ini diperoleh nilai μ terbaik untuk perkiraan TDOA menggunakan algoritma LMS adaptif pada pelacakan posisi paus lodan adalah 0.01. Kata kunci— perkiraan TDOA, LMS adaptif, faktor konvergensi, pelacakan paus lodan AbstractResearch on TDOA estimation in sperm whale tracking has been done [1] that uses the Teager - Kaiser operator in improving accuracy the TDOA estimation using adaptive LMS algorithm on sperm whale tracking. However, further researches on the right convergence factor (μ) (fast and accurate) in TDOA estimation using adaptive LMS algorithms for sperm whale tracking have not been performed. Will be analyzed the TDOA estimation using adaptive LMS algorithm in sperm whale tracking with the variation of μ. As a reference to determine the right value of μ, the results of sperm whale tracking[2] is used.TDOA estimation using Adaptive LMS algorithm was first published by Benesty [3]. The approach taken is based on estimation of the impulse responses from source to receivers. In the adaptive LMS algorithm function updates the coefficient with μ as adaptation step. TDOA values obtained from the difference between the two impulse responses.From the results, values changing of μ affect the speed of TDOA estimation using the LMS adaptive algorithm. However, the wrong value of μ is lead to inaccurate sperm whale tracking results. The best value of μ for TDOA estimation using the LMS adaptive algorithm for sperm whale tracking is 0.01. Keywords— TDOA estimation, adaptive LMS, convergence factor, sperm whale tracking
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Yaro, Abdulmalik Shehu, Ahmad Zuri Sha'ameri e Sa’id Musa Yarima. "Direct and Indirect TDOA Estimation based Multilateration System Position Estimation Accuracy Comparison". ELEKTRIKA- Journal of Electrical Engineering 20, n. 1 (30 aprile 2021): 54–64. http://dx.doi.org/10.11113/elektrika.v20n1.226.

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Multilateration (MLAT) system estimate aircraft position from its electromagnetic emission using time difference of arrival (TDOA) estimated at ground receiving station (GRS)s with a lateration algorithm. The position estimation (PE) accuracy of the MLAT system depends on several factors one of which is the TDOA estimation approach. In this paper, the PE performance of a minimum configuration 3-dimensional (3-D) MLAT system based on the direct and indirect approaches to TDOA estimation is presented. The analysis is carried out using Monte Carlo simulation with the transmitter and receiver parameters based on an actual system used in the civil aviation. Simulation results show that within 150 km radius, the direct TDOA based MLAT system performs better than the indirect TDOA based MLAT system. Beyond 150 km radius, the indirect TDOA based MLAT system has the least PE error compared the direct TDOA based MLAT system. Further comparison of the MLAT system based on the two TDOA estimation approaches with other surveillance systems shows that the direct TDOA based MLAT system has the least PE error within 150 km radius while long-range aircraft PE beyond 150 km, automatic surveillance dependent broadcast (ADS-B) outperformed the MLAT system as it has the least PE error
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Più fonti

Tesi sul tema "TDOA"

1

Bennett, Granger Hart. "Acoustic transient TDOA estimation and discrimination". Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2000. http://handle.dtic.mil/100.2/ADA384321.

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Thesis (M.S. in Electrical Engineering and M.S. in Engineering Acoustics) Naval Postgraduate School, September 2000.
Thesis advisor(s): Therrien, Charles W. ; Tummala, Murrali ; Smith, Kevin B. "September 2000." Includes bibliographical references (p. 57-58). Also available online.
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2

Arbring, Joel, e Patrik Hedström. "On Data Compression for TDOA Localization". Thesis, Linköping University, Information Coding, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-57274.

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This master thesis investigates different approaches to data compression on common types of signals in the context of localization by estimating time difference of arrival (TDOA). The thesis includes evaluation of the compression schemes using recorded data, collected as part of the thesis work. This evaluation shows that compression is possible while preserving localization accuracy.

The recorded data is backed up with more extensive simulations using a free space propagation model without attenuation. The signals investigated are flat spectrum signals, signals using phase-shift keying and single side band speech signals. Signals with low bandwidth are given precedence over high bandwidth signals, since they require more data in order to get an accurate localization estimate.

The compression methods used are transform based schemes. The transforms utilized are the Karhunen-Loéve transform and the discrete Fourier transform. Different approaches for quantization of the transform components are examined, one of them being zonal sampling.

Localization is performed in the Fourier domain by calculating the steered response power from the cross-spectral density matrix. The simulations are performed in Matlab using three recording nodes in a symmetrical geometry.

The performance of localization accuracy is compared with the Cramér-Rao bound for flat spectrum signals using the standard deviation of the localization error from the compressed signals.

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3

Humpherys, Brian. "SIGNAL TDOA BASED HIGH RESOLUTION TSPI". International Foundation for Telemetering, 1994. http://hdl.handle.net/10150/608843.

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International Telemetering Conference Proceedings / October 17-20, 1994 / Town & Country Hotel and Conference Center, San Diego, California
This paper describes a method for determining high resolution time, space, and position information for a test range flight vehicle using four tracking receivers. Equipped with GPS time systems, each receiver records the exact time at which a time marker embedded in the transmitted TM data stream is received. With this information, the time difference of arrival for the time markers at three of the receivers can be calculated referenced to the fourth. Using this time difference, the position of the transmitter can be determined. The accuracy with which the received signal time delay can be calculated depends on the accuracy of the GPS time system at each receiver. The effect of time accuracy on positional resolution is evaluated.
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4

Nan, Xie, e Zhang Futang. "Performance Analysis of Reentry TDOA Positioning System". International Foundation for Telemetering, 2009. http://hdl.handle.net/10150/606140.

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ITC/USA 2009 Conference Proceedings / The Forty-Fifth Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2009 / Riviera Hotel & Convention Center, Las Vegas, Nevada
In reentry measurement, we need to measure the track of reentry vehicle. For the speed of target is very high, it is difficult for traditional positioning system to capture and track the target. TDOA (time difference of arrival) positioning system is used in reentry measurement. The position of target is calculated by using time difference of arrival. This paper introduces the principle of reentry TDOA positioning system. The key technology is synchronization of ground stations' clocks. The implementation of clock synchronization using low-cost commercial GPS receiver is presented. The sources of errors in the existing telemetry system, corresponding precision and experimental results are presented. Some methods, which are used to improve the precision, are proposed at the end of this paper.
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5

Kovavisaruch, La-or. "Source localization using TDOA with erroneous receiver positions". Diss., Columbia, Mo. : University of Missouri-Columbia, 2005. http://hdl.handle.net/10355/6278.

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Thesis (Ph. D.)--University of Missouri-Columbia, 2005.
The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (May 22, 2006) Vita. Includes bibliographical references.
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6

Bressner, Thomas Arthur Herbert. "Development and Evaluation of UTDoAas a Positioning Method in LTE". Thesis, KTH, Signalbehandling, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-176499.

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Although positioning has been one of the main target study areas in mobile communication in the last decade, it still receives strong attention in recent years focusing more on the indoor users. Nowadays, a wide range of different methods are available to estimate the position of the target user under certain circumstances. One of these methods is Uplink Time Difference of Arrival (UTDoA), which has been defined in 3GPP Release 11 for Long Term Evolution (LTE) networks, and is the focus of this master thesis. In Uplink based positioning, to estimate the position of a User Equipment (UE), the UE only needs to generate and transmit the reference signal and the main computational effort of time estimation, is moved from the UE towards the network side. This might be one advantage compared to Observed Time Difference of Arrival (OTDoA), while further performance properties of UTDoA in LTE are investigated in the course of this master thesis. In parallel with the 3GPP Study Item on Indoor Positioning which mainly was based on downlink OTDoA, this thesis studies on the potential use of UTDoA in LTE under the same type of agreed deployment scenarios and simulation parameters. For time estimation based on the Sounding Reference Signals (SRSs), the uplink channel has been modeled and simulated. Finally, the position estimation of the UE is derived by multilateration techniques using the time/distance estimations of the received SRS at each eNodeB. The metrics of positioning results are based on Cumulative Distribution Functions (CDF) of horizontal and vertical positioning error. The study shows that reasonable horizontal position accuracy can be achieved, while a number of pico cells are added to the network to enhance the macro-only scenario. However, this positive effect could not be observed in vertical position estimation. A further investigated aspect is the influence by other active UEs considered as interference. The outcome shows, that the accuracy is strongly and negatively affected by introducing interference. A final observation focuses on the SRS bandwidth and that for bandwidths below 10 MHz additional degradations in performance are seen.
Trots att positionering har varit ett av huvudmålen för forskning inom mobil kommunikation under det senaste decenniet, får det fortfarande mycket uppmärksamhet och under de senaste åren har forskningen fokuserats mer på inomhusanvändare. Idag finns en mängd olika metoder för att estimera positionen för en specifik användare under vissa omständigheter. En av dessa metoder är Uplink Time Difference of Arrival (UTDoA) som har definierats i 3GPP Release 11 för Long Term Evolution (LTE)-nätverk och är fokus för detta examensarbete. I positionering baserad på upplänken, vilken används för att skatta positionen för en User Equipment (UE), behöver UE:n bara generera och sända en referenssignal och den huvudsakliga beräkningskraften för tidsestimeringen flyttas från UE:n till nätsidan. Detta kan vara en fördel jämfört med Observed Time Difference of Arrival (OTDoA), detta examensarbete undersöker ytterligare prestandaegenskaper hos UTDoA i LTE. Parallellt med 3GPP:s studie för inomhuspositionering, som huvudsakligen baseras på nerlänk OTDoA, studerar denna avhandling den potentiella användningen av UTDoA i LTE med samma typ av överenskomna scenarier och simuleringsparametrar. För tidsuppskattning baserad på Sounding Reference Signals (SRSs) har kanalen upplänkmodellerats och simulerats. Slutligen är positionsestimeringen av UE:n härledd genom multilaterationstekniker med hjälp av tids- och distansestimeringar av de mottagna SRS vid varje eNodeB. De mått som används för positioneringsresultat baseras på kumulativ fördelningsfunktion av det horisontella och vertikala positioneringsfelet. Studien visar att en rimlig noggrannhet kann uppnås i den horisontella dimensionen då ett antal pico-celler adderas till nätverket för att förbättra makroscenariot. Denna positiva effekt kunde emellertid inte observeras i den vertikala positionsestimeringen. En ytterligare undersökt aspekt är påverkan av andra aktiva UEs, som betraktas som interferens. Resultaten visar att noggrannheten är starkt negativt påverkad då störningar i form av interferens införs. En slutlig observation fokuserar på bandbredden av SRS och det visar på försämringar i prestanda för bandbredder under 10 MHz.
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Basciftci, Cagri Halis. "Direction Finding With Tdoa In A Multipath Land Environment". Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608756/index.pdf.

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In this thesis, the problem of Angle of Arrival estimation of radar signals with Time Difference of Arrival method in an outdoor land multipath environment with limited line of sight is analyzed. A system model is proposed. Effects of system, channel and radar parameters on the Angle of Arrival estimation performance are investigated through Monte Carlo simulations. Improving effect of utilization of diversity on the estimation performance is observed. Performances of the space diversity with noncoherent and selective combining are compared. Finally a realistic scenario is studied and performance of the proposed system is investigated.
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8

Li, Binghao Surveying &amp Spatial Information Systems Faculty of Engineering UNSW. "Terrestial mobile user positioning using TDOA and fingerprinting techniques". Awarded by:University of New South Wales. School of Surveying and Spatial Information Systems, 2006. http://handle.unsw.edu.au/1959.4/25507.

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Specialists are expecting the knowledge of location will trigger yet another revolution in mobile services. Location-base services (LBS) have attracted many researchers and enterprises and one of the key aspects of LBS is positioning technology. Considering a wider and more complex field - ubiquitous computing, location is the fundamental element. This work focuses on some aspects of the new techniques of terrestrial positioning systems. Wireless LAN is one of the most popular systems used for positioning for indoor environments and public places. We have investigated the trilateration and fingerprinting approaches and the results showed the advantages of fingerprinting. A novel method to generate the fingerprints database based on Universal Kriging (UK) was developed, which can not only significantly decrease the training time, but also increase the accuracy of estimates. In mobile phone positioning systems, most techniques suffer from the non-line-of-sight (NLOS) propagation. We investigated the specifics of NLOS error, and proposed a method to mitigate the errors. Furthermore, a new algorithm named WSMM (wireless signal map matching) was discussed. Simulations and experiments verified the idea, and the accuracy of positioning can be improved greatly. Since fingerprinting technique can utilize rather than suffer from the NLOS propagation, it was also applied in mobile phone positioning system. Experiments showed both the deterministic approach and probabilistic approach can provide better results comparing with other techniques in suburban area. To achieve a robust positioning system and provide more useful information of the user, multisensor combination and data fusion are necessary. As the first step of future research, a mulitsensor synchronization system was developed. This system can promisingly achieve synchronization with error less than 0.4 ms, which is suitable for most land applications. Hence the main findings of this thesis are: (1) a novel method of yielding fingerprint database for both wireless LAN (WLAN) and mobile phone systems when using the fingerprinting technique for positioning; (2) a database method to mitigate NLOS error for mobile phone positioning systems; (3) a low cost synchronization system for integration of multiple sensors.
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KATAYAMA, Masaaki, Takaya YAMAZATO e Jan Mateusz KIETLINSKI-ZALESKI. "TDoA UWB Positioning with Three Receivers Using Known Indoor Features". IEEE, 2010. http://hdl.handle.net/2237/14480.

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Aktas, Unal. "Time difference of arrival (TDOA) estimation using wavelet based denoising". Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1999. http://handle.dtic.mil/100.2/ADA360774.

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Thesis (M.S. in Electrical Engineering) Naval Postgraduate School, March 1999.
"March 1999" Thesis advisor(s): David V. Lamm, Michael W. Boudreau. Includes bibliographical references (p. 103-104). Also available online.
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Libri sul tema "TDOA"

1

Bennett, Granger Hart. Acoustic transient TDOA estimation and discrimination. Monterey, Calif: Naval Postgraduate School, 2000.

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2

Haney, Timothy N. Generation of Global System for Mobile (GSM) signals and their Time Difference of Arrival (TDOA) estimation. Monterey, Calif: Naval Postgraduate School, 2000.

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3

G, Glisic Savo, e Leppänen Pentti A, a cura di. Wireless communications: TDMA versus CDMA. Boston: Kluwer Academic Publishers, 1997.

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Glisic, Savo G. Wireless Communications: TDMA versus CDMA. Boston, MA: Springer US, 1997.

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5

Coursey, Cameron. Understanding digital PCS: The TDMA standard. Boston: Artech House, 1999.

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6

Adrian, Smith, e Jacobs Charles A, a cura di. IS-136 TDMA technology, economics, and services. Boston: Artech House, 1998.

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L, Jou, Lenart J e United States. National Aeronautics and Space Administration., a cura di. Study of optoelectronic switch for SS-TDMA: Final report. Waltham, MA: GTE Laboratories Inc., 1989.

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National Institute of Standards and Technology (U.S.), a cura di. Recommendation for the Triple Data Encryption Algorithm (TDEA) block cipher. Gaithersburg, MD: U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 2004.

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Fouad, Abousamra, Baric Ante, Civili Francesco Saverio, United Nations Environment Programme, United Nations Environment Programme. Mediterranean Action Plan. e Global Environment Facility, a cura di. Transboundary diagnostic analysis, TDA, for the Mediterranean Sea. Athens: UNEP/MAP/MED POL, 2005.

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illustrateur, Morin Jean 1959, a cura di. Le TDA/H raconté aux enfants: J'ai un quoi? Boucherville, Québec: Éditions de Mortagne, 2016.

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Capitoli di libri sul tema "TDOA"

1

Seong, Nak-Seon, e Seong-Ook Park. "Clock Offsets in TDOA Localization". In Ubiquitous Computing Systems, 111–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11890348_9.

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Kistanov, Pavel, Elizaveta Shcherbinina, Alexander Titov, Oleg Tsarik e Igor Tsikin. "Direct TDOA Based Positioning in Satellite Geolocation". In Springer Proceedings in Physics, 729–38. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58868-7_79.

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Gambi, J. M., M. C. Rodriguez-Teijeiro e M. L. Garcia del Pino. "The Post-Newtonian Geolocation Problem by TDOA". In Mathematics in Industry, 489–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25100-9_56.

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Liu, Guangzhe, Jingyu Hua, Feng Li, Weidang Lu e Zhijiang Xu. "A Quadratic Programming Localization Based on TDOA Measurement". In Lecture Notes in Electrical Engineering, 1243–50. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6504-1_148.

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Burgess, Simon, Yubin Kuang, Johannes Wendeberg, Kalle Åström e Christian Schindelhauer. "Minimal Solvers for Unsynchronized TDOA Sensor Network Calibration". In Algorithms for Sensor Systems, 95–110. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-45346-5_8.

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Lee, S. C., W. R. Lee e K. H. You. "TDoA Based UAV Localization Using Dual-EKF Algorithm". In Communications in Computer and Information Science, 47–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10741-2_6.

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Shao, Hongshuo, Dongkyun Kim e Kwanho You. "TDOA/FDOA Geolocation with Adaptive Extended Kalman Filter". In Communications in Computer and Information Science, 226–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17625-8_23.

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Li, Wenquan, e Bing Zhao. "Analysis of TDOA Location Algorithm Based on Ultra-Wideband". In Lecture Notes in Electrical Engineering, 1257–61. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-13-9409-6_149.

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Li, Peihua, e Xianzhe Ma. "Robust Acoustic Source Localization with TDOA Based RANSAC Algorithm". In Emerging Intelligent Computing Technology and Applications, 222–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04070-2_25.

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Huang, Bohao, Shuo Gu e Wei Xia. "A Model of Cloud Computing-Based TDOA Location System". In Wireless Communications, Networking and Applications, 1187–94. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2580-5_108.

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Atti di convegni sul tema "TDOA"

1

Feng, Xuefeng, Zhen Huang, Jiazhi He e Lei Shi. "A Moving Source Localization Method Based on TDOA and TDOA Rate". In 2021 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC). IEEE, 2021. http://dx.doi.org/10.1109/icspcc52875.2021.9564741.

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2

Panetta, Chandler J., Osama N. Ennasr e Xiaobo Tan. "Distributed Particle Filter With Online Model Learning for Localization Using Time-Difference-of-Arrival (TDOA) Measurements". In ASME 2020 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/dscc2020-3305.

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Abstract The problem of localizing a moving target arises in various forms in wireless sensor networks. Deploying multiple sensing receivers and using the time-difference-of-arrival (TDOA) of the target’s emitted signal is widely considered an effective localization technique. Traditionally, TDOA-based algorithms adopt a centralized approach where all measurements are sent to a predefined reference node for position estimation. More recently, distributed TDOA-based localization algorithms have been shown to improve the robustness of these estimates. For target models governed by highly stochastic processes, the method of nonlinear filtering and state estimation must be carefully considered. In this work, a distributed TDOA-based particle filter algorithm is proposed for localizing a moving target modeled by a discrete-time correlated random walk (DCRW). We present a method for using data collected by the particle filter to estimate the unknown probability distributions of the target’s movement model, and then apply the distribution estimates to recursively update the particle filter’s propagation model. The performance of the distributed approach is evaluated through numerical simulation, and we show the benefit of using a particle filter with online model learning by comparing it with the non-adaptive approach.
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Wendeberg, Johannes, Fabian Hoflinger, Christian Schindelhauer e Leonard Reindl. "Anchor-free TDOA self-localization". In 2011 International Conference on Indoor Positioning and Indoor Navigation (IPIN). IEEE, 2011. http://dx.doi.org/10.1109/ipin.2011.6071909.

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4

Bandiera, Francesco, Angelo Coluccia, Giuseppe Ricci, Fabio Ricciato e Danilo Spano. "TDOA Localization in Asynchronous WSNs". In 2014 12th IEEE International Conference on Embedded and Ubiquitous Computing (EUC). IEEE, 2014. http://dx.doi.org/10.1109/euc.2014.35.

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Acar, Yusuf, Yusuf Onur, Umut Gundogdu, Mustafa Erseven e Cihangir Erdem. "TDOA Based Hybrid Localization Algorithm". In 2022 30th Signal Processing and Communications Applications Conference (SIU). IEEE, 2022. http://dx.doi.org/10.1109/siu55565.2022.9864695.

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Malcic, Boris, Slavko Sajic, Milan Trifunovic e Vedran Jovanovic. "Asynchronous 2D-TDOA Localization Method". In 2021 29th Telecommunications Forum (TELFOR). IEEE, 2021. http://dx.doi.org/10.1109/telfor52709.2021.9653271.

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He, Entong, Yuxiang Yang e Chenshu Wu. "Quantum Ranging Enhanced TDoA Localization". In ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2024. http://dx.doi.org/10.1109/icassp48485.2024.10446684.

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Amineh, Reza Ashrafi, e Ali Asghar Beheshti Shirazi. "Estimation of User Location in 4G Wireless Networks Using Cooperative TDoA/RSS/TDoA Method". In 2014 International Conference on Communication Systems and Network Technologies (CSNT). IEEE, 2014. http://dx.doi.org/10.1109/csnt.2014.127.

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Chang-jiang, Liu, Wang Chao-feng e LE Dan. "Influence of Correction for Atmospheric Refraction in passive TDOA location on system TDOA error". In 2019 International Conference on Control, Automation and Information Sciences (ICCAIS). IEEE, 2019. http://dx.doi.org/10.1109/iccais46528.2019.9074561.

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Xu, Jun, Maode Ma e Choi Law. "Position Estimation Using UWB TDOA Measurements". In 2006 IEEE International Conference on Ultra-Wideband. IEEE, 2006. http://dx.doi.org/10.1109/icu.2006.281617.

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Rapporti di organizzazioni sul tema "TDOA"

1

Fowler, Mark L. Data Compression Trade-Offs for TDOA/FDOA Geo-Location Systems. Fort Belvoir, VA: Defense Technical Information Center, febbraio 2008. http://dx.doi.org/10.21236/ada483204.

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2

Hippenstiel, Ralph D., Timothy Haney e Tri T. Ha. Improvement of the Time Difference of Arrival (TDOA) Estimation of GSM Signals Using Wavelets. Fort Belvoir, VA: Defense Technical Information Center, giugno 2000. http://dx.doi.org/10.21236/ada380368.

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3

Hippenstiel, Ralph D., Tri T. Ha e Unal Aktas. Localization of Wireless Emitters Based on the Time Difference of Arrival (TDOA) and Wavelet Denoising. Fort Belvoir, VA: Defense Technical Information Center, maggio 1999. http://dx.doi.org/10.21236/ada363100.

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Arumugam, Mahesh, e Sandeep S. Kulkarni. Self-Stabilizing Deterministic TDMA for Sensor Networks. Fort Belvoir, VA: Defense Technical Information Center, gennaio 2006. http://dx.doi.org/10.21236/ada455715.

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Bednar, Amy. Topological data analysis : an overview. Engineer Research and Development Center (U.S.), giugno 2021. http://dx.doi.org/10.21079/11681/40943.

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A growing area of mathematics topological data analysis (TDA) uses fundamental concepts of topology to analyze complex, high-dimensional data. A topological network represents the data, and the TDA uses the network to analyze the shape of the data and identify features in the network that correspond to patterns in the data. These patterns extract knowledge from the data. TDA provides a framework to advance machine learning’s ability to understand and analyze large, complex data. This paper provides background information about TDA, TDA applications for large data sets, and details related to the investigation and implementation of existing tools and environments.
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Berry, D. A. [TDA`s hot gas desulfurization sorbent]. TDA Inc./FETC CRADA No. 97-F003, final report. Office of Scientific and Technical Information (OSTI), novembre 1997. http://dx.doi.org/10.2172/629371.

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Hoffman, L. G. Technology development, evaluation, and application (TDEA) FY 1997 progress report. Office of Scientific and Technical Information (OSTI), maggio 1998. http://dx.doi.org/10.2172/663508.

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Kulkarni, Sandeep S., e Mahesh Arumugam. Infuse: A TDMA Based Data Dissemination Protocol for Sensor Networks. Fort Belvoir, VA: Defense Technical Information Center, novembre 2004. http://dx.doi.org/10.21236/ada460202.

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Barker, W. C., e E. B. Barker. Recommendation for the triple data encryption algorithm (TDEA) block cipher. Gaithersburg, MD: National Institute of Standards and Technology, 2012. http://dx.doi.org/10.6028/nist.sp.800-67r1.

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Barker, Elaine, e Nicky Mouha. Recommendation for the Triple Data Encryption Algorithm (TDEA) block cipher. Gaithersburg, MD: National Institute of Standards and Technology, novembre 2017. http://dx.doi.org/10.6028/nist.sp.800-67r2.

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