scholarly journals A Study of Positioning Capabilities of Post Interferometric Processing Between Single Frequency GPS Receiver Observation Data and Permanent GPS Station Data

2014 ◽  
Vol 53 (1) ◽  
pp. 39-43
Author(s):  
Kazuyoshi TAKAHASHI ◽  
Hiroki IRIE ◽  
Takahiro YAMADA
Keyword(s):  
Single Frequency ◽  
Observation Data ◽  
Gps Receiver ◽  
Station Data ◽  
Gps Station

scholarly journals High-precision coseismic displacement estimation with a single-frequency GPS receiver

2015 ◽  
Vol 202 (1) ◽  
pp. 612-623 ◽  
Author(s):  
Bofeng Guo ◽  
Xiaohong Zhang ◽  
Xiaodong Ren ◽  
Xingxing Li
Keyword(s):  
High Precision ◽  
Single Frequency ◽  
Gps Receiver ◽  
Coseismic Displacement ◽  
Displacement Estimation

Detection of Spoofing Attack using Machine Learning based on Multi-Layer Neural Network in Single-Frequency GPS Receivers

2017 ◽  
Vol 71 (1) ◽  
pp. 169-188 ◽  
Author(s):  
E. Shafiee ◽  
M. R. Mosavi ◽  
M. Moazedi
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Late Phase ◽  
Machine Learning Algorithms ◽  
Computational Method ◽  
Single Frequency ◽  
Detection Accuracy ◽  
Gps Receiver ◽  
Navigation Data ◽  
Spoofing Detection

The importance of the Global Positioning System (GPS) and related electronic systems continues to increase in a range of environmental, engineering and navigation applications. However, civilian GPS signals are vulnerable to Radio Frequency (RF) interference. Spoofing is an intentional intervention that aims to force a GPS receiver to acquire and track invalid navigation data. Analysis of spoofing and authentic signal patterns represents the differences as phase, energy and imaginary components of the signal. In this paper, early-late phase, delta, and signal level as the three main features are extracted from the correlation output of the tracking loop. Using these features, spoofing detection can be performed by exploiting conventional machine learning algorithms such as K-Nearest Neighbourhood (KNN) and naive Bayesian classifier. A Neural Network (NN) as a learning machine is a modern computational method for collecting the required knowledge and predicting the output values in complicated systems. This paper presents a new approach for GPS spoofing detection based on multi-layer NN whose inputs are indices of features. Simulation results on a software GPS receiver showed adequate detection accuracy was obtained from NN with a short detection time.

scholarly journals Assessment of the position accuracy of a single-frequency GPS receiver designed for electromagnetic induction surveys

2018 ◽  
Vol 20 (1) ◽  
pp. 19-39 ◽  
Author(s):  
Sebastian Rudolph ◽  
Ben Paul Marchant ◽  
Lutz Weihermüller ◽  
Harry Vereecken
Keyword(s):  
Electromagnetic Induction ◽  
Single Frequency ◽  
Gps Receiver ◽  
Position Accuracy

scholarly journals Analysis of the Spatiotemporal Change in Land Surface Temperature for a Long-Term Sequence in Africa (2003–2017)

2020 ◽  
Vol 12 (3) ◽  
pp. 488 ◽  
Author(s):  
Nusseiba NourEldeen ◽  
Kebiao Mao ◽  
Zijin Yuan ◽  
Xinyi Shen ◽  
Tongren Xu ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Observation Data ◽  
The West ◽  
Thermal Infrared Remote Sensing ◽  
Ground Station ◽  
Station Data ◽  
Effects Of Temperature ◽  
Reconstruction Model

It is very important to understand the temporal and spatial variations of land surface temperature (LST) in Africa to determine the effects of temperature on agricultural production. Although thermal infrared remote sensing technology can quickly obtain surface temperature information, it is greatly affected by clouds and rainfall. To obtain a complete and continuous dataset on the spatiotemporal variations in LST in Africa, a reconstruction model based on the moderate resolution imaging spectroradiometer (MODIS) LST time series and ground station data was built to refactor the LST dataset (2003–2017). The first step in the reconstruction model is to filter low-quality LST pixels contaminated by clouds and then fill the pixels using observation data from ground weather stations. Then, the missing pixels are interpolated using the inverse distance weighting (IDW) method. The evaluation shows that the accuracy between reconstructed LST and ground station data is high (root mean square er–ror (RMSE) = 0.84 °C, mean absolute error (MAE) = 0.75 °C and correlation coefficient (R) = 0.91). The spatiotemporal analysis of the LST indicates that the change in the annual average LST from 2003–2017 was weak and the warming trend in Africa was remarkably uneven. Geographically, “the warming is more pronounced in the north and the west than in the south and the east”. The most significant warming occurred near the equatorial region in South Africa (slope > 0.05, R > 0.61, p < 0.05) and the central (slope = 0.08, R = 0.89, p < 0.05) regions, and a nonsignificant decreasing trend occurred in Botswana. Additionally, the mid-north region (north of Chad, north of Niger and south of Algeria) became colder (slope > −0.07, R = 0.9, p < 0.05), with a nonsignificant trend. Seasonally, significant warming was more pronounced in winter, mostly in the west, especially in Mauritania (slope > 0.09, R > 0.9, p < 0.5). The response of the different types of surface to the surface temperature has shown variability at different times, which provides important information to understand the effects of temperature changes on crop yields, which is critical for the planning of agricultural farming systems in Africa.

Extracting Ionosphere Scintillations Index Based on Single Frequency GPS Software Receiver

2012 ◽  
Vol 190-191 ◽  
pp. 1136-1143
Author(s):  
Zhi Huang ◽  
Hong Yuan ◽  
Qi Yao Zuo
Keyword(s):  
High Speed ◽  
Single Frequency ◽  
Scintillation Index ◽  
Ionospheric Scintillation ◽  
Signal Acquisition ◽  
Gps Receiver ◽  
Signal Loss ◽  
Software Receiver ◽  
Ionospheric Plasma Density ◽  
Gps Signal Acquisition

Scintillations are caused by ionospheric plasma-density irregularities and can lead to signal power fading, loss of lock of the carrier tracking loop in the GPS receiver. The traditional method of monitoring and mitigating scintillation is to transform commercial GPS receiver with modified hardware and embedded software. To better facilitate advance development GPS receiver under different condition, GPS software scintillation receiver is designed in this paper. The hardware scheme of high-speed GPS signal acquisition system is first discussed and implemented with FPGA and DSP architecture. Then, we describe receiver software processing algorithm, particularly the portion involving the scintillation signal acquisition and tracking, ionospheric scintillation index extracting and scintillation monitoring. The performance of software receiver is demonstrated under scintillation conditions. Relevant results show that software-receiver based approach can avoid weak signal loss and extract effectively ionospheric scintillation parameter compared with the traditional extracting method. Software receiver is suitable and reliable for the ionospheric scintillations monitoring, and can provide theoretical foundations and experimental preparations for future scintillation studies implemented with Chinese indigenous BeiDou-Ⅱ navigation and poisoning system.

GPS RECEIVERS TIMING DATA PROCESSING USING NEURAL NETWORKS: OPTIMAL ESTIMATION AND ERRORS MODELING

2007 ◽  
Vol 17 (05) ◽  
pp. 383-393 ◽  
Author(s):  
M. R. MOSAVI
Keyword(s):  
Neural Networks ◽  
Outdoor Recreation ◽  
Optimal Estimation ◽  
Single Frequency ◽  
Gps Receiver ◽  
Commercial Aviation ◽  
Gps Receivers ◽  
Before And After ◽  
Timing Data

The Global Positioning System (GPS) is a network of satellites, whose original purpose was to provide accurate navigation, guidance, and time transfer to military users. The past decade has also seen rapid concurrent growth in civilian GPS applications, including farming, mining, surveying, marine, and outdoor recreation. One of the most significant of these civilian applications is commercial aviation. A stand-alone civilian user enjoys an accuracy of 100 meters and 300 nanoseconds, 25 meters and 200 nanoseconds, before and after Selective Availability (SA) was turned off. In some applications, high accuracy is required. In this paper, five Neural Networks (NNs) are proposed for acceptable noise reduction of GPS receivers timing data. The paper uses from an actual data collection for evaluating the performance of the methods. An experimental test setup is designed and implemented for this purpose. The obtained experimental results from a Coarse Acquisition (C/A)-code single-frequency GPS receiver strongly support the potential of methods to give high accurate timing. Quality of the obtained results is very good, so that GPS timing RMS error reduce to less than 120 and 40 nanoseconds, with and without SA.

scholarly journals Slow strain waves in blocky geological media from GPS and seismological observations on the Amurian plate

2016 ◽  
Author(s):  
Victor G. Bykov ◽  
Sergei V. Trofimenko
Keyword(s):  
Active Faults ◽  
Periodic Variation ◽  
Observation Data ◽  
Strain Waves ◽  
Crustal Block ◽  
Amurian Plate ◽  
Block Movement ◽  
Observation Series ◽  
New Evidence ◽  
Gps Station

Abstract. Based on the statistical analysis of spatiotemporal distribution of earthquake epicenters and perennial geodetic observation series, new evidence is obtained for the existence of slow strain waves in the Earth. The results of our investigation allow us to identify the dynamics of seismicity along the northern boundary of the Amurian plate as a wave process. Migration of epicenters of weak earthquakes (2 ≤ М ≤ 4) is initiated by the east-west propagation of a strain wave front at an average velocity of 2.7 km/day. We have found a synchronous quasi-periodic variation of seismicity in equally spaced clusters with spatial periods of 3.5° and 7.26° comparable with the length of slow strain waves. The geodetic observations at GPS sites in proximity to local active faults show that in a number of cases, the GPS site coordinate seasonal variations exhibit a significant phase shift, whereas the time series of these GPS sites differ significantly from a sinusoid. Based on experimental observation data and the developed model of crustal block movement we have shown that there is one possible interpretation for this fact that the trajectory of GPS station position disturbance is induced by migrating of crustal deformation in the form of slow waves.

scholarly journals An Enhanced Method for Detecting and Repairing the Cycle Slips of Dual-Frequency Onboard GPS Receivers of LEO Satellites

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Zhouming Yang ◽  
Xin Liu ◽  
Jinyun Guo ◽  
Yaowei Xia ◽  
Xiaotao Chang
Keyword(s):  
Weighted Least Squares ◽  
Observation Equation ◽  
Single Frequency ◽  
Observation Data ◽  
Cycle Slip ◽  
Dual Frequency ◽  
Gps Receivers ◽  
Cycle Slips ◽  
Reference Satellite ◽  
Leo Satellites

Cycle slip detection and repair play important roles in the processing of data from dual-frequency GPS receivers onboard low-Earth orbit (LEO) satellites. To detect and repair cycle slips more comprehensively, an enhanced error method (EEM) is proposed. EEM combines single-frequency and narrow-lane carrier phase observations to construct special observations and observation equation groups. These special observations differ across time and satellite (ATS). ATS observations are constructed by three steps. The first step is differencing single-frequency and narrow-lane observations through a time difference (TD). The second step is to select a satellite as a reference satellite and other satellites as nonreference satellites. The third step is to difference the single-frequency TD observations from the reference satellite and the narrow-lane TD observations from the nonreference satellites by a satellite difference. If cycle slips occur at the reference satellite, the correction values for these ATS observations can be significantly enlarged. To process all satellites, the EEM selects each satellite as a reference satellite and builds the corresponding equation group. The EEM solves these observation equation groups according to the weighted least-squares adjustment (LSA) criterion and obtains the correction values; these correction values are then used to construct the χ 2 values corresponding to different equation groups, and the EEM subsequently carries out a chi-square distribution test for these χ 2 . The satellite corresponding to the maximum χ 2 will be marked. Then, the EEM iteratively processes the other satellites. Cycle slips can be estimated by rounding the float solutions of changes in the ambiguities of cycle slip satellites to the nearest integer. The simulation test results show that the EEM can be used to detect special cycle slip pairs such as (1, 1) and (9, 7). The EEM needs only observation data in two adjacent epochs and is still applicable to observation epochs with continuous cycle slips.

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