Synergy Between Global Positioning System Code, Carrier, and Signal-to-Noise Ratio Multipath Errors

With the widespread use of indoor positioning technology, various services based on this technology are beginning to be offered to consumers and industrial applications. In the case of logistics facilities, in addition to indoor and outdoor spaces, there are top-bounded spaces (TBSs): elongated areas that are covered with roofs or eaves on the upper parts of buildings. The sides of such spaces are open, and workers and forklifts work in these areas. Only a few studies have been conducted on positioning methods for this unusual environment, and the way by which Signal-to-Noise Ratio (SNR) of Global Positioning System (GPS) changes with the stay in TBSs is unclear. Therefore, we conducted preliminary experiments and confirmed that TBS dwellings are difficult to stably detect with existing methods due to the combination of satellites with variable and unchanged SNRs. In this study, we designed a simple processing flow for selecting satellites with high probabilities of changing SNRs by using the spatial characteristics of TBSs as parameters (height, depth, and side opening orientation). We propose a method to detect the stay in TBSs using the SNR change rates of the selected satellites. As a result of evaluation experiments with three TBSs, we successfully detected the stay in TBSs with about 30% higher probability than those of an existing method.

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A system level implementation of wavelet based filtering for GNSS signals

10.32920/ryerson.14650077 ◽

2021 ◽

Author(s):

Jorge Leon

Keyword(s):

Wavelet Analysis ◽

Global Positioning System ◽

Cross Correlation ◽

Position Estimation ◽

System Level ◽

Positioning System ◽

Wavelet Filter ◽

Detail Design ◽

Global Positioning ◽

Multipath Errors

A project is presented to study the Global Positioning System and learn how to apply wavelet analysis to mitigate the effects of multipath errors on GNSS signals. The analysis is carried out using the SystemC language to demonstrate how one may try to implement the GPS signal wavelet filter in hardware. Wavelet analysis, the SystemC library and additional tools are discussed in detail. Design issues such as control signaling and position estimation are explained. System evaluation is performed at two levels, one using cross correlation of signals and the second by measuring the amount of clustering in position plots.

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Global Positioning System Interferometric Reflectometry for Accurate Tide Gauge Measurement: Insights from South Beach, Oregon, United States

10.20944/preprints202002.0142.v1 ◽

2020 ◽

Author(s):

Kutubuddin Ansari ◽

Tae-Suk Bae ◽

Samed Inyurt

Keyword(s):

Global Positioning System ◽

Sea Water ◽

Tide Gauge ◽

Signal To Noise Ratio ◽

Moving Average ◽

Singular Spectrum Analysis ◽

Autoregressive Moving Average ◽

Positioning System ◽

Observation Network ◽

Global Positioning

Global Positioning System (GPS) stations located along coastal areas have the ability to measure tide gauge (TG) records by reflected signal reception from the sea water surface. In this study we used the GPS signal-to-noise ratio (SNR) data from the SEPT station (44.63 ⁰N, 124.05 ⁰W) located at South Beach, Oregon, USA, to estimate the TG records using only a few measurements. First, we derived the TG record from a GPS station (GPS-TG) and used traditional TG data from the National Water Level Observation Network (NWLON) sentinel station (Station ID: 9435380) located in Oregon for validation purposes because it was closest to the SEPT station. Our results show that the GPS-TG and NWLON-TG correlate well with the correlation coefficient (CC) of 0.942 and the root mean square (RMS) of their residuals was about 12.90 cm. The corresponding TG prediction by autoregressive moving average (ARMA-TG) and singular spectrum analysis (SSA-TG) models are evaluated for their effectiveness over the station. The comparative analysis demonstrates that the GPS-TG has improved correlation with ARMA-TG (CC of ~0.981 CC, RMS of ~4.80 cm), and SSA-TG (CC of ~0.998 CC, RMS of ~ 0.88 cm) compared to the NWLON-TG (CC of ~0.942 CC, RMS of ~12.90 cm) values. We believe the outcomes from this study contribute to a better understanding of the numerical modeling of TG records as well as other measurements based on reflectometry techniques.

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A system level implementation of wavelet based filtering for GNSS signals

10.32920/ryerson.14650077.v1 ◽

2021 ◽

Author(s):

Jorge Leon

Keyword(s):

Wavelet Analysis ◽

Global Positioning System ◽

Cross Correlation ◽

Position Estimation ◽

System Level ◽

Positioning System ◽

Wavelet Filter ◽

Detail Design ◽

Global Positioning ◽

Multipath Errors

A project is presented to study the Global Positioning System and learn how to apply wavelet analysis to mitigate the effects of multipath errors on GNSS signals. The analysis is carried out using the SystemC language to demonstrate how one may try to implement the GPS signal wavelet filter in hardware. Wavelet analysis, the SystemC library and additional tools are discussed in detail. Design issues such as control signaling and position estimation are explained. System evaluation is performed at two levels, one using cross correlation of signals and the second by measuring the amount of clustering in position plots.

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Mitigation of Ionospheric Scintillation on Global Positioning System (GPS) Using Hamming and Convolutional Coding Techniques

FUOYE Journal of Engineering and Technology ◽

10.46792/fuoyejet.v1i1.3 ◽

2016 ◽

Vol 1 (1) ◽

Author(s):

Festus K Ojo ◽

Damilare O Akande ◽

Babatunde S Daniel

Keyword(s):

Global Positioning System ◽

Satellite Communication ◽

Signal To Noise Ratio ◽

Power Level ◽

Research Work ◽

Ionospheric Scintillation ◽

Error Correction Codes ◽

Positioning System ◽

Convolutional Coding ◽

Global Positioning

The Global Positioning System (GPS) is a satellite-based system that can be used to locate positions anywhere on the earth surface. Any person with a GPS receiver can access the system, and it can be used for application that requires location coordinates. Currently, ionospheric scintillation is the largest error source in GPS. Scintillation causes some effects such as degradation of receiver tracking performance and in extreme cases, total loss of navigation capabilities. Ionospheric scintillation is a problem for satellite communication because it affects the amplitude and phase of radio signals. A decrease in the amplitude of a radio signal reduces its power level which directly affects the signal to noise ratio, thus affecting a base station's ability to detect and receive the signal. Error correction codes techniques are applied in almost all digital systems as they provide better performance for dealing with the unwanted signal (noise). This research work has investigated the performance of hamming and convolutional coding techniques in mitigating error in GPS signal modeled in MATLAB/Simulink by transmitting randomly generated data through a Rayleigh fading channel. The performance metric employed in evaluating the system is Bit Error Rate (BER). The simulation results showed a comparison of the BER performance of the uncoded and coded signals (using Hamming and Convolutional coding techniques).

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Estimating velocity from noisy GPS data for investigating the temporal variability of slope movements

Natural Hazards and Earth System Science ◽

10.5194/nhess-14-2503-2014 ◽

2014 ◽

Vol 14 (9) ◽

pp. 2503-2520 ◽

Cited By ~ 15

Author(s):

V. Wirz ◽

J. Beutel ◽

S. Gruber ◽

S. Gubler ◽

R. S. Purves

Keyword(s):

Global Positioning System ◽

Temporal Variability ◽

Synthetic Data ◽

Gps Data ◽

Positioning System ◽

Signal To Noise ◽

Slope Movements ◽

Global Positioning ◽

System Data ◽

Full Knowledge

Abstract. Detecting and monitoring of moving and potentially hazardous slopes requires reliable estimations of velocities. Separating any movement signal from measurement noise is crucial for understanding the temporal variability of slope movements and detecting changes in the movement regime, which may be important indicators of the process. Thus, methods capable of estimating velocity and its changes reliably are required. In this paper we develop and test a method for deriving velocities based on noisy GPS (Global Positioning System) data, suitable for various movement patterns and variable signal-to-noise-ratios (SNR). We tested this method on synthetic data, designed to mimic the characteristics of diverse processes, but where we have full knowledge of the underlying velocity patterns, before applying it to explore data collected.

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Determination of the Best Emulsion for the Microscopy of Crystals

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100096886 ◽

1981 ◽

Vol 39 ◽

pp. 32-33

Author(s):

David A. Grano ◽

Kenneth H. Downing

Keyword(s):

Spatial Frequency ◽

Information Transfer ◽

Signal To Noise Ratio ◽

Experimental Situation ◽

Photographic Emulsion ◽

Modulation Transfer ◽

Signal To Noise ◽

Frequency Space ◽

Noise Ratio

The retrieval of high-resolution information from images of biological crystals depends, in part, on the use of the correct photographic emulsion. We have been investigating the information transfer properties of twelve emulsions with a view toward 1) characterizing the emulsions by a few, measurable quantities, and 2) identifying the “best” emulsion of those we have studied for use in any given experimental situation. Because our interests lie in the examination of crystalline specimens, we've chosen to evaluate an emulsion's signal-to-noise ratio (SNR) as a function of spatial frequency and use this as our critereon for determining the best emulsion.The signal-to-noise ratio in frequency space depends on several factors. First, the signal depends on the speed of the emulsion and its modulation transfer function (MTF). By procedures outlined in, MTF's have been found for all the emulsions tested and can be fit by an analytic expression 1/(1+(S/S0)2). Figure 1 shows the experimental data and fitted curve for an emulsion with a better than average MTF. A single parameter, the spatial frequency at which the transfer falls to 50% (S0), characterizes this curve.

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Experiments in Bright-Field Imaging with Hollow-Cone Illumination

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100097703 ◽

1981 ◽

Vol 39 ◽

pp. 226-227

Author(s):

W. Kunath ◽

K. Weiss ◽

E. Zeitler

Keyword(s):

Signal To Noise Ratio ◽

Carbon Support ◽

Electronic System ◽

Optic Axis ◽

Hollow Cone ◽

Signal To Noise ◽

Bright Field ◽

Noise Ratio ◽

Single Field ◽

Field Imaging

Bright-field images taken with axial illumination show spurious high contrast patterns which obscure details smaller than 15 ° Hollow-cone illumination (HCI), however, reduces this disturbing granulation by statistical superposition and thus improves the signal-to-noise ratio. In this presentation we report on experiments aimed at selecting the proper amount of tilt and defocus for improvement of the signal-to-noise ratio by means of direct observation of the electron images on a TV monitor.Hollow-cone illumination is implemented in our microscope (single field condenser objective, Cs = .5 mm) by an electronic system which rotates the tilted beam about the optic axis. At low rates of revolution (one turn per second or so) a circular motion of the usual granulation in the image of a carbon support film can be observed on the TV monitor. The size of the granular structures and the radius of their orbits depend on both the conical tilt and defocus.

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Information capacity and bandwidth limitations in the SEM

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100152392 ◽

1989 ◽

Vol 47 ◽

pp. 84-85

Author(s):

D. C. Joy ◽

R. D. Bunn

Keyword(s):

Signal To Noise Ratio ◽

Critical Dimension ◽

Information Capacity ◽

Acquisition Time ◽

Signal To Noise ◽

Sem Image ◽

Probe Size ◽

Minimum Number ◽

Noise Ratio ◽

Signal Channel

The information available from an SEM image is limited both by the inherent signal to noise ratio that characterizes the image and as a result of the transformations that it may undergo as it is passed through the amplifying circuits of the instrument. In applications such as Critical Dimension Metrology it is necessary to be able to quantify these limitations in order to be able to assess the likely precision of any measurement made with the microscope.The information capacity of an SEM signal, defined as the minimum number of bits needed to encode the output signal, depends on the signal to noise ratio of the image - which in turn depends on the probe size and source brightness and acquisition time per pixel - and on the efficiency of the specimen in producing the signal that is being observed. A detailed analysis of the secondary electron case shows that the information capacity C (bits/pixel) of the SEM signal channel could be written as :

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