Determination of global positioning system (GPS) receiver clock errors: impact on positioning accuracy

2009 ◽  
Vol 20 (7) ◽  
pp. 075105 ◽  
Author(s):  
Ta-Kang Yeh ◽  
Cheinway Hwang ◽  
Guochang Xu ◽  
Chuan-Sheng Wang ◽  
Chien-Chih Lee
2012 ◽  
Vol 263-266 ◽  
pp. 346-349 ◽  
Author(s):  
Hong Shi ◽  
Dong Hai Qiao

Geophysical measurement relies on the positioning accuracy of GPS (global positioning system). Usually the positioning accuracy is area dependent. This paper uses a commercially available GPS receiver to verify its positioning accuracy with practical measurement in a small area. With a measurement setup in an open ground, the results show that even for the fixed point, the GPS measured positioning error of about 0.234 meter could be observed for a period of time. Of 12 GPS measured distance errors, only one is about 5.7 meters, all others are within the range of 3-5 meters of GPS receiver specification.


2013 ◽  
Vol 6 (1) ◽  
pp. 767-793
Author(s):  
A. Barreto ◽  
E. Cuevas ◽  
B. Damiri ◽  
P. M. Romero ◽  
F. Almansa

Abstract. In this paper we present the preliminary results of atmospheric column integrated water vapor (PWV) obtained with a new Lunar Cimel photometer (LC) at the high mountain Izaña Observatory in the period July–August, 2011. We have compared nocturnal PWV from LC with PWV from a Global Positioning System (GPS) receiver and nighttime radiosondes (RS92). LC data have been calibrated using the Lunar Langley Method (LLM). We complemented this comparative study using quasi-simultaneous daytime PWV from Cimel AERONET (CA), GPS and RS92. Comparison of daytime PWV from CA shows differences against GPS and RS92 up to 0.18 cm. Two different filters, with and approximate bandwidth of 10 nm and central wavelengths at 938 nm (Filter#1) and 937 nm (Filter#2), were mounted into the LC. Filter#1 is currently used in operational AERONET sunphotometers. PWV obtained with LC-Filter#1 showed an overestimation above 0.18 and 0.25 cm compared to GPS and RS92, respectively, meanwhile Filter#2, with a reduced out-of-band radiation, showed very low differences compared with the same references (≤0.03 cm). These results demonstrate the ability of the new lunar photometer to obtain accurate and continuous PWV measurements at night in addition to the notably influence of the filter's transmissivity response on PWV determination at nighttime. The use of enhanced bandpass filters in lunar photometry, which is affected by more important inaccuracies than sun-photometry, is necessary to infer PWV with similar precision than AERONET.


1992 ◽  
Vol 19 (14) ◽  
pp. 1487-1490 ◽  
Author(s):  
Yvonne Vigue ◽  
Stephen M. Lichten ◽  
Geoffrey Blewitt ◽  
Michael B. Heflin ◽  
Rajendra P. Malla

Author(s):  
P.J. Zabinski ◽  
B.K. Gilbert ◽  
P.J. Zucarelli ◽  
D.V. Weninger ◽  
T.W. Keller

Author(s):  
Thobias Sando ◽  
Renatus Mussa ◽  
John Sobanjo ◽  
Lisa Spainhour

Global positioning system (GPS) has been identified as a potential tool for capturing crash location data. This study quantifies factors that could affect the accuracy of GPS receivers. The results showed that GPS receiver orientation, site obstructions, and weather have significant effects on the accuracy of GPS receivers. Time of day and number of satellites were not found to significantly affect the accuracy of GPS receivers. HDOP values of 1.2 or less were found to be adequate for crash location purposes. An accuracy improvement of 20.7% was realized by filtering GPS data based on HDOP values.


2019 ◽  
Vol 9 (1) ◽  
pp. 6 ◽  
Author(s):  
Masood Varshosaz ◽  
Alireza Afary ◽  
Barat Mojaradi ◽  
Mohammad Saadatseresht ◽  
Ebadat Ghanbari Parmehr

Spoofing of Unmanned Aerial Vehicles (UAV) is generally carried out through spoofing of the UAV’s Global Positioning System (GPS) receiver. This paper presents a vision-based UAV spoofing detection method that utilizes Visual Odometry (VO). This method is independent of the other complementary sensors and any knowledge or archived map and datasets. The proposed method is based on the comparison of relative sub-trajectory of the UAV from VO, with its absolute replica from GPS within a moving window along the flight path. The comparison is done using three dissimilarity measures including (1) Sum of Euclidian Distances between Corresponding Points (SEDCP), (2) angle distance and (3) taxicab distance between the Histogram of Oriented Displacements (HOD) of these sub-trajectories. This method can determine the time and location of UAV spoofing and bounds the drift error of VO. It can be used without any restriction in the usage environment and can be implemented in real-time applications. This method is evaluated on four UAV spoofing scenarios. The results indicate that this method is effective in the detection of UAV spoofing due to the Sophisticated Receiver-Based (SRB) GPS spoofing. This method can detect UAV spoofing in the long-range UAV flights when the changes in UAV flight direction is larger than 3° and in the incremental UAV spoofing with the redirection rate of 1°. Additionally, using SEDCP, the spoofing of the UAV, when there is no redirection and only the velocity of the UAV is changed, can be detected. The results show that SEDCP is more effective in the detection of UAV spoofing and fake GPS positions.


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