NEUTRINO PHYSICS AT SHORT BASELINE

2006 ◽  
Author(s):  
ERIC D. ZIMMERMAN
Keyword(s):  
Neutrino Physics ◽  
Short Baseline

NEUTRINO PHYSICS AT SHORT BASELINE

2006 ◽  
Vol 21 (08n09) ◽  
pp. 1869-1874
Author(s):  
ERIC D. ZIMMERMAN
Keyword(s):  
Neutrino Physics ◽  
Cross Section ◽  
Neutrino Oscillation ◽  
Systematic Errors ◽  
Positive Signal ◽  
Short Baseline ◽  
Neutrino Cross Section

Neutrino oscillation searches at short baseline (defined as ≲ 1 km) have investigated oscillations with Δm2 ≳ 0.1 eV 2. One positive signal, from the LSND collaboration, exists and is being tested by the MiniBooNE experiment. Neutrino cross-section measurements are being made, which will be important for reducing systematic errors in present and future oscillation measurements.

Ultra Short Baseline (USBL) Calibration for Positioning of Underwater Objects

2019 ◽  
Vol 2 (2) ◽  
pp. 73-85
Author(s):  
Bagus Septyanto ◽  
Dian Nurdiana ◽  
Sitti Ahmiatri Saptari
Keyword(s):  
Acoustic Wave ◽  
Scale Factor ◽  
Positioning System ◽  
Radio Waves ◽  
Short Baseline ◽  
Error Angle ◽  
Satellite Navigation System ◽  
The Earth ◽  
Underwater Positioning ◽  
Radio Signals

In general, surface positioning using a global satellite navigation system (GNSS). Many satellites transmit radio signals to the surface of the earth and it was detected by receiver sensors into a function of position and time. Radio waves really bad when spreading in water. So, the underwater positioning uses acoustic wave. One type of underwater positioning is USBL. USBL is a positioning system based on measuring the distance and angle. Based on distance and angle, the position of the target in cartesian coordinates can be calculated. In practice, the effect of ship movement is one of the factors that determine the accuracy of the USBL system. Ship movements like a pitch, roll, and orientation that are not defined by the receiver could changes the position of the target in X, Y and Z coordinates. USBL calibration is performed to detect an error angle. USBL calibration is done by two methods. In USBL calibration Single Position obtained orientation correction value is 1.13 ̊ and a scale factor is 0.99025. For USBL Quadrant calibration, pitch correction values is -1.05, Roll -0.02 ̊, Orientation 6.82 ̊ and scale factor 0.9934 are obtained. The quadrant calibration results deccrease the level of error position to 0.276 - 0.289m at a depth of 89m and 0.432m - 0.644m at a depth of 76m

О ТОЧНОСТИ ОПРЕДЕЛЕНИЯ КООРДИНАТ ПОДВОДНОГО МОДУЛЯ НА ОСНОВЕ ИЗМЕРЕННЫХ ПАРАМЕТРОВ ДВИЖЕНИЯ БУКСИРУЕМОЙ СИСТЕМЫ

2020 ◽  
Author(s):  
V.V. Kostenko ◽  
Yu.V. Vaulin ◽  
F.S. Dubrovin ◽  
O.Yu. Lvov
Keyword(s):  
Immersion Depth ◽  
Computational Algorithms ◽  
Navigation Systems ◽  
Short Baseline ◽  
Positioning Accuracy ◽  
Underwater Acoustic ◽  
Ground Speed ◽  
Cable Length ◽  
Acoustic Navigation

Буксируемый подводный модуль (БПМ) эффективно используется для решения задач, связанных с координированием подводных объектов, местоположение которых подлежит уточнению в процессе их детальногообследования. При этом большое значение имеет точность определения координат самого буксируемогомодуля относительно судна-буксировщика. Использование гидроакустических навигационных средств, вчастности систем с ультракороткой базой (ГАНС УКБ), ограничено вследствие помех, влияющих на качествосигналов в приемной антенне. Альтернативой служит метод определения координат БПМ на основе данныхтраекторных измерений параметров буксируемой системы. К числу последних относятся расчетные значенияпараметров кабеля связи в установившихся режимах буксировки, значения путевой скорости и путевого углабуксировщика, а также измеренные значения длины кабеля, глубины погружения и курса БПМ. В работе дансравнительный анализ различных вариантов вычислительных алгоритмов, позволяющих получить оценки точности определения координат БПМ в различных режимах стационарной буксировки и при наличии сбоев вработе навигационных средств.The towed underwater module (TUM) is a useful toolfor solving problems of the positioning of the underwaterobjects, the location of which must be clarified during its detailedinspection. Herewith, the accuracy of the determinationof the coordinates of the towed module itself relative tothe towing vessel is essential for such kind of problems. Theuse of underwater acoustic navigation means, the systemswith ultra-short baseline (USBL) in particular, are limiteddue to interference affecting the quality of the signals on thereceiving antenna. As an alternative, the method is proposedfor TUM positioning based on trajectory measurements ofparameters of the towed system, which may include calculatedvalues of communication cable parameters in steadystatetowing modes, values of ground speed and towing angle,as well as measured cable length, immersion depth, andTUM heading. The paper provides a comparative analysisof various versions of computational algorithms, which allowobtaining estimates of the TUM positioning accuracy indifferent modes of stationary towing and in the presence offailures in navigation systems operation.

scholarly journals Improved short-baseline neutrino oscillation search and energy spectrum measurement with the PROSPECT experiment at HFIR

2021 ◽  
Vol 103 (3) ◽  
Author(s):  
M. Andriamirado ◽  
A. B. Balantekin ◽  
H. R. Band ◽  
C. D. Bass ◽  
D. E. Bergeron ◽  
...  
Keyword(s):  
Energy Spectrum ◽  
Neutrino Oscillation ◽  
Short Baseline ◽  
Spectrum Measurement

GPS-BDS-Galileo double-differenced stochastic model refinement based on least-squares variance component estimation

2021 ◽  
pp. 1-16
Author(s):  
Hong Hu ◽  
Xuefeng Xie ◽  
Jingxiang Gao ◽  
Shuanggen Jin ◽  
Peng Jiang
Keyword(s):  
Stochastic Model ◽  
Least Squares ◽  
Stochastic Models ◽  
Variance Component ◽  
Satellite System ◽  
Variance Component Estimation ◽  
Short Baseline ◽  
Component Estimation ◽  
Zero Baseline ◽  
Global Navigation Satellite

Abstract Stochastic models are essential for precise navigation and positioning of the global navigation satellite system (GNSS). A stochastic model can influence the resolution of ambiguity, which is a key step in GNSS positioning. Most of the existing multi-GNSS stochastic models are based on the GPS empirical model, while differences in the precision of observations among different systems are not considered. In this paper, three refined stochastic models, namely the variance components between systems (RSM1), the variances of different types of observations (RSM2) and the variances of observations for each satellite (RSM3) are proposed based on the least-squares variance component estimation (LS-VCE). Zero-baseline and short-baseline GNSS experimental data were used to verify the proposed three refined stochastic models. The results show that, compared with the traditional elevation-dependent model (EDM), though the proposed models do not significantly improve the ambiguity resolution success rate, the positioning precision of the three proposed models has been improved. RSM3, which is more realistic for the data itself, performs the best, and the precision at elevation mask angles 20°, 30°, 40°, 50° can be improved by 4⋅6%, 7⋅6%, 13⋅2%, 73⋅0% for L1-B1-E1 and 1⋅1%, 4⋅8%, 16⋅3%, 64⋅5% for L2-B2-E5a, respectively.

scholarly journals Empirical Stochastic Model of Multi-GNSS Measurements

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4566
Author(s):  
Dominik Prochniewicz ◽  
Kinga Wezka ◽  
Joanna Kozuchowska
Keyword(s):  
Stochastic Model ◽  
Density Ratio ◽  
Functional Model ◽  
Optimal Solution ◽  
Global Navigation Satellite Systems ◽  
Unknown Parameters ◽  
Short Baseline ◽  
Stochastic Parameters ◽  
Dependent Model ◽  
The Impact

The stochastic model, together with the functional model, form the mathematical model of observation that enables the estimation of the unknown parameters. In Global Navigation Satellite Systems (GNSS), the stochastic model is an especially important element as it affects not only the accuracy of the positioning model solution, but also the reliability of the carrier-phase ambiguity resolution (AR). In this paper, we study in detail the stochastic modeling problem for Multi-GNSS positioning models, for which the standard approach used so far was to adopt stochastic parameters from the Global Positioning System (GPS). The aim of this work is to develop an individual, empirical stochastic model for each signal and each satellite block for GPS, GLONASS, Galileo and BeiDou systems. The realistic stochastic model is created in the form of a fully populated variance-covariance (VC) matrix that takes into account, in addition to the Carrier-to-Noise density Ratio (C/N0)-dependent variance function, also the cross- and time-correlations between the observations. The weekly measurements from a zero-length and very short baseline are utilized to derive stochastic parameters. The impact on the AR and solution accuracy is analyzed for different positioning scenarios using the modified Kalman Filter. Comparing the positioning results obtained for the created model with respect to the results for the standard elevation-dependent model allows to conclude that the individual empirical stochastic model increases the accuracy of positioning solution and the efficiency of AR. The optimal solution is achieved for four-system Multi-GNSS solution using fully populated empirical model individual for satellite blocks, which provides a 2% increase in the effectiveness of the AR (up to 100%), an increase in the number of solutions with errors below 5 mm by 37% and a reduction in the maximum error by 6 mm compared to the Multi-GNSS solution using the elevation-dependent model with neglected measurements correlations.

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