Science topic

Global Navigation Satellite System - Science topic

A satellite navigation or SAT NAV system is a system of satellites that provide autonomous geo-spatial positioning with global coverage. A satellite navigation system with global coverage may be termed a global navigation satellite system or GNSS. Global coverage for each system is generally achieved by a satellite constellation of 20–30 medium Earth orbit (MEO) satellites spread between several orbital planes. The actual systems vary, but use orbit inclinations of >50° and orbital periods of roughly twelve hours (at an altitude of about 20,000 kilometres (12,000 mi)).
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It seems it is common to combine basic observations to create new observable, which are then used for PPP and other applications. Basic observations such as pseudorange and carrier-phase observations are real measurement from GNSS. These real observations are combined to create entirely new observable which is not direct, physical, and real. Amazingly, these new observable solves the real problem such as PPP (e.g. Ionosphere -free combination).
  • What is the theory behind this?
  • Any similar approach like this in other scientific field or any simple analogous explanation?
  • You could direct me to resources such as videos, or literature.
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furthermore, one a satellite is locked for recording the phases, a counter starts, keep add "1" to the number in the counter whenever a whole cycle carrier wave is passed based on the time a wave length corresponds to. So, the unknow ambiguity of a satellite maintains constant (associated with the time instant when the lock starts) as long as this satellite is being locked without interruption. In case an interruption, a different ambiguity will have to be resolved in the estimation.
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I have 3D position of few of GNSS stations obtained from AUSPOS service in ITRF2014 frame. I have 3D position of same stations from CSRS-PPP service in ITRF2020 reference frame. I want to transform ITRF2014 position into ITRF2020 position to compare the results. I came to know the transformation parameters to move from ITRF2014 to ITRF2020 are available in IERS website. However, I needed an explanation on how to achieve this such as brief theoretical overview, softwares or scripts that does this job, any walk-through resources e.g. document or videos that streamlined this process.
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Thank you very much professor Wolfgang R. Dick
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Hello everyone! As you understand, high-precision positioning using global navigation satellite systems or simply high-precision determination of a random variable. At what point does your estimates precision fall into the "highly precision" category? Is this always a convention associated with the method of determining a random variable or is there a general formulation for classifying estimates as highly precision?
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The precision of a class must be defined by specifications, which define the RMS and the instruments to be used. If there are no specifications, then people involved in such a class get together and decide about the specifications for the class.
The number of digits also characterizes the precision of an instrument. If a theodolite measures an angle with a direct reading of one second, its precision is one second. If you want to test it you measure several times the three angles of a triangle, and you see how much the closing error is.
In any case, you define precision by specifications; you test precision by statistical analysis of measurements of a well-designed experiment.
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Hey there, I am working on a project that involves the bending angle, temperature, and pressure anomalies from the COSMIC-2 datasets. I have extracted the data for the 14th 15th and 16th of January but there are too many files nearly 6k netCDF files. I need anomalies for specific coordinates so how can we do that? I know how to extract data from netCDF files but I just need an efficient way to get data for my desired coordinates without reading all the files one by one.
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Although I have some experience in all sorts of data wrangling, I have never processed COSMIC-2 files themselves.
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I have postprocessed GNSS data of Santiago Chilo eartquake (2010) in PPP mode in RTKLIB. I am intending to look at the comparative analysis of accuracy of the positioning solutions of PPP static and PPP kinematic, from this event data, but could not figure out what should i look to answer this research question. How can I solve this research question?
I have attached the following figures to give you quick insight into the results of ppp static and ppp kinematic.
The visualization shows that the PPP Kinematic is able to show the large release of stress on the tectonic plate at 6.40 UTC (the time at which big shaking of plate did happen for all coordinate components, on which Santiago, Chile the permanent site is located) which is not obtained in the plot obtained from ppp static. However, rms value for ppp static is much smaller than PPP kinematic here in these two plots.
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Shaolin Lü,yes the dataset is open.I had analyzed the high-rated GPS data from SANT GPS station of Chile, with respect to the 57th, 58th, and 59th day (Julian days) of 2010, which was related to the great Chile Earthquake 2010.
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If you have an area of several 25's of acres (several 100,000 m²) and your only source of GNSS Information is that of the drone, can there be distortion of the 3D Model / orthomosaic that are so large that calculations based on this model cannot be trusted?
In other words: Do GCPs not only add global georeferenced accuracy, but also decrease the error of the scale of the result (for example if you want to measure landfill, the surface area or the volume of some rocks or debris) ?
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Yes, without GCPs and RTK/PPK, it is highly possible to obtain wrong or inaccurate geometric information in UAV-based photogrammetric mapping. When dealing with large areas, relying solely on the drone's GNSS information can lead to distortions in the 3D model or orthomosaic. GCPs not only add global georeferenced accuracy but also help decrease errors in the scale of the results, making them essential for reliable measurements.
The accuracy of UAS-based photogrammetric mapping depends on several factors, including Ground Control Points (GCPs), flight height, camera resolution, GNSS accuracy of the device, weather conditions, processing software, user experience, etc. While it is possible to obtain satisfactory 3D models without GCPs or RTK/PPK, for precise measurements such as surface area or volume calculations, GCPs are essential. For more in-depth information, you can refer to my MSc thesis and the following articles. In the following studies, you can find comparisons of processing with and without GCPs as well.
MSc Thesis:
Good luck on your journey of exploration and innovation!
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In IGS website, only GPS precise orbit is available. I want to perform PPP analysis with multi-GNSS combination which requires precise orbit of other constellations along with GPS orbits. How can I get precise orbit for GALILEO, GLONASS, BDS etc?
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Hi Shanker,
You can get those from individual Analysis Centers (ACs) at CDDIS, while their GPS products are generally then combined into a single IGS product.
Attached here an example (multi-GNSS orbits & clocks):
Folder [e.g. GPS Week 2259]
File [e.g. CODE MGEX Final product for DOY 115 in 2023]
> COD0MGXFIN_20231150000_01D_05M_ORB.SP3.gz
ps. MGEX = Multi-GNSS Experiment (https://igs.org/mgex/)
Regards,
Lotfi.
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We are trying to perform PPP analysis for 1h observation period. Is 1h of data sufficient for doing PPP analysis?
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I think it is possible because the ambiguity fixed time is roughly around 30min. And if no cyclic slip occurs, the 1h data could be available for preliminary analysis.
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how far can i take gravity assist manoeuvre and how it works?
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Thank you very much @mustafa kamil
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What is the range of values of ionospheric delay and its uncertainty in GNSS positioning?
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In order to have an accurate position solution the ionospheric effect need to be mitigated; different approaches can be used depending on the receiver characteristics. In particular, ionospheric error can be reduced using multi-frequency measurements, exploiting corrections provided by an augmentation system, relying on a model such as Klobuchar, NeQUick, NTCM. In the first approach, the dispersive nature of the ionosphere is exploited: the ionospheric effect is mitigated using a linear combination of measurements from two frequencies. Although, this approach allows to remove up to 99% of the ionospheric error it requires the use of a multi-frequency receiver that is in general more expensive than a single frequency device; in addition, the combination of the measurements lead to an increased measurement noise. Single frequency devices could limit the ionospheric error using an augmentation system like European Geostationary Navigation Overlay Service (EGNOS) or Wide Area Augmentation System (WAAS) ; these systems broadcast ionospheric correction for specific coverage areas. With this approach, a receiver needs access the correction through an internet connection or processing the Satellite Based Augmentation System (SBAS) signals adding complexity to the device and to the processing chain. Single frequency stand-alone devices need to mitigate the ionospheric error using a model. Recently, an empirical model Neustrelitz Total Electron Content Model for Galileo (NTCM G) has been proposed as an alternative to Klobuchar and NeQuick-G (currently adopted by GPS and Galileo, respectively). The three models exploits different approaches and have different characteristics: Klobuchar model is quite simple to implement and it is able to correct up to 50% of the ionospheric error; some advantages have been demonstrated when using the NeQuick-G model, which is able to correct up to 70% of the ionospheric error but it has an higher computation load.
So the accuracy with which you can estimate the iono delay is function of the strategy adopted and the model used. Finally, in case of disturbances the discrepancy between the estimation and the current iono delay could be very large.
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As till now after the matched filter or correlator we get a projection of vector and now with with Maxmimum liklehood AND with MAP criteria how we arrive to decission ?
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Hello, I am a researcher working on GNSS Interferometric Reflectometry (GNSS-IR). The signal segments we work on may not always contain many waves. Hence, I need an expert opinion on how I should proceed in such a situation. My questions are as follows:
  1. How many full waves are required to accurately estimate the frequency of a signal segment?
  2. Is there a conventional criterion for the minimum number of waves?
  3. Is it possible to express the accuracy of an estimated frequency with a quantity derived from the spectra or periodogram (such as the peak width)?
Thank you in advance for your answers and suggestions.
Regards.
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I suppose that the interferometric signal is available as a train of equidistant samples. In such case, the most flexible and also precise method for the frequency analysis is the discrete Fourier transform (DFT), the most common algorithm is the fast Fourier transform (FFT). Its output is a discrete frequency spectrum ranging from 0 to the Nyquist frequency, i.e. the half of the sampling rate f_s (f_Nyquist = f_s/2). The frequency spectrum is discrete, the frequency steps have the magnitude of delta_f = 1/T, where T is the length of the acquired data set in seconds.
As Jim Prater wrote in his post, the acquired data set can be observed as a multiplication of the original data multiplied by a square window with a width equal to T. In the frequency domain, you will see a convolution of the original frequency spectrum and the Fourier transform of the square window. The latter one is the sinc function, i.e. a sharp frequency peak (a delta function) in the original spectrum will be converted to a sinc function. The width of such peak is about 2-3 x delta_f, this implies that just by looking at the spectral data, you can determine the signal frequency with a precision of delta_f.
If you have acquired just a few signal periods, the precision is not exciting. If the signal contains, for instance, 3 periods, the frequency spectrum will contain a peak with the maximum at the index of 3, i.e. the frequency is (3±0.5) x delta_f. People usually fit the sinc function to the spectral data and obtain the real frequency with a better precision than ±0.5 x delta_f. There is, however, a much more elegant method that can be used here, it is called zero filling. You simply append zeros to the original data and increase the length of the data set in this way before you run the FFT algorithm. It increases the frequency resolution and improves the precision significantly. The peak does not contain of a few points more so that one can easily find its maximum. One can even fit a parabolic function to the peak around its maximum to further enhance the resolution. What improvement can be reached in practice is dependent on the noise in the acquired signal. If the noise is weak, one can improve the frequency resolution by many orders of magnitude. To get the answer you want, one has to simulate it or use the real data and just look for the results.
There is one point more that has to be mentioned: The sinc function is not the best peak shape that one can imagine. It has a lot of side bands, i.e. a single peak in the original spectrum results in many peaks in the calculated data. The side bands can obscure real peaks in the original spectrum, but if just a single peak is expected, they should not matter much. To improve the peak shape if complex spectra have to be analyzed, dedicated apodization or window functions were developed. One multiplies the data with such function before the FFT is calculated, i.e. one replaces the default square window by another function. One of the best ones is the Blackman-Harris polynomial with 4 terms, its side bands are about 5 orders of magnitude weaker than the main peak, i.e. under normal conditions, they are below the noise floor and therefore, not more visible in the resulting spectrum. Since the apodization generally increases the peak width, it must be carefully chosen since it can decrease the frequency resolution or obscure double peaks.
There are also much simpler methods that can be used for frequency determination but they cannot reach the precision of the Fourier transform. One of the methods is often used by frequency counters, where the time points are analyzed where the signal crosses the zero line or another other level. One can fit a linear function to them and obtain the frequency from the line slope. Since such method uses just a few data points from the whole data set, it is much more sensitive to noise and cannot reach the precision of the FFT which uses all available data. The main drawback of the FFT analysis is its complexity, it requires a lot of computational power and data memory - especially if data sets containing millions of samples have to be converted. For shorter data sets, the required resources are usually not critical and the results are excellent.
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I enter to:
and I got the following 4 directories:
  • STD_FC/
  • STD_OP/
  • VMF1_FC/
  • VMF1_OP/
What is the meaning of each directory?
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Yes. Thank you very much Junsheng Ding .
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How can I determine tropospheric dealy at give location (latitude, longitude, height) from VMF?
How can I access VMF using python?
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Shanker KC The Vienna Mapping Function (VMF) is a mathematical model that represents the mapping between the zenith hydrostatic delay and the entire zenith delay of the Earth's atmosphere (zenith hydrostatic delay plus zenith wet delay).
The geographical location of the site (latitude, longitude, and elevation above sea level) and the day of the year are fed into the VMF.
The overall zenith delay of the atmosphere at the location, including the zenith hydrostatic delay and the zenith wet delay, is the output of the VMF. Subtract the zenith hydrostatic delay from the overall zenith delay to obtain the tropospheric delay from the VMF output.
The VMF is commonly used in geodetic and geophysical applications such as GPS location and satellite altimetry to compensate for the effects of the Earth's atmosphere on distance and height measurements.
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How does this ionospheric-free linear combination work?
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Because the ionospheric delays (and extra pseudo ranges or phases) differ at different frequencies, but the true distances are the same, by combining two equations you could exclude one variable. See "Eliminating the effect of the TEC" in Hofmann-Wellenhof et al. (2008).
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Major earthquake events can cause ground deformation which can be detectable by GNSS. After a large event, GNSS data can even be used to improve moment magnitude estimations.
For smaller magnitude events, I was wondering what would be the threshold for magnitude/distance from the earthquake source that we can detect the earthquake's coseismic (+postseismic signal) signature on the GNSS time series.
On Nevada Geodetic Laboratory website (http://geodesy.unr.edu/NGLStationPages/stations/LEMN.sta), I saw this formula: "10^(M/2 - 0.79)", we input magnitude (M) to obtain distance value (km). If the distance between the GNSS station and the earthquake epicenter is less than the value we obtained from the formula, it is possible to see a step record on the GNSS time series.
I would really appreciate it if someone could recommend some papers related to this topic.
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Here is an article:
Perhaps onto base of formula used by article writer you can create a formula useful for you... same see the critics of the forecasting method:
You really have to pay attention to the geological structure of the zone... as is written in the article
Regards,
Laszlo
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I have downloaded the 7 days GNSS observation data from one of the UNAVCO listed CORS station. So there are 7 different 24h files for each day for the same CORS station. Can I perform PPP in RTKLIB using all 7 days 24h files at the same time? If so how can I do that?
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#### Basic Approach
When setting the path to the PPP datasets:
-obs
-brdm
-sp3
-clk
you may use any of the following parsers (these are general keywords):
##########################################################
%Y ==> yyyy : four-digit year (2000-2099)
%y ==> yy : two-digit year (00-99)
%m ==> mm : month (01-12)
%d ==> dd : day of month (01-31)
%h ==> hh : hours (00-23)
%H ==> a : hour code (a-x)
%M ==> mm : minutes (00-59)
%n ==> ddd : day of year (DOY, 001-366)
%W ==> wwww : gps week (0001-9999)
%D ==> d : day of gps week (0-6)
%N ==> d : sequence number (0- )
%s ==> ssss : station name (lower-case)
%S ==> SSSS : station name (upper-case)
%r ==> rrrr : station name
##########################################################
For example, for your task, you may set the DOY for multi-day processing or the station name for multi-station processing.
Note: Remember to list the station names in the processing
scheme.
For example:
-karo
-mzuz
-ctpm
-vwzm
-...
#### Advanced Approach
You may write a program to call the following:
-PPP configuration file
-rnx2rtkp
The processing program may be written in
-Bash
-Python
-Julia
-...
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I am currently working on GNSS Spoofing as my master's thesis and working on GPS signal generation using MATLAB.
I wanted to know whether it is possible to use MATLAB for generating a complete signal of 5 satellites or not?
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Thank you so much for your kind responses. I have completed my Masters thesis and got an A grade on my thesis too. :)
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Inside RTKPOST software, there is various positioning modes available. Among, three are: PPP Static, PPP Fixed, & PPP Kinematic. How is one different from another?
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The major difference is how to handle the position parameters in the filter. In PPP-Fixed mode, the position parameters are constrainted to the priori coordinates with a rather small variance, so its estimates almost does not change no matter the observations good or bad. PPP-Static mode consider the position parameter as a random random constant parameter, whose variance-covariance will decrease as the observation accumulation. Hence its position estimates will convergent to a certain value since the contribution of the new observations decrease. PPP Kinematic mode consider the position parameter as random variables, whose variance-covariance will be re-initialized every epoch. Hence its estimates will be noiser than the other two mode, but it is necessary for processing kinematic data unless you have other information like IMU observations.
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If the geodetic coordinates (φ,λ,h) of the ground station (e.g., GPS station) is known, how can the pressure, temperature, and relative humidity of this station be predicted at different times?. I'm looking for a mathematical model+modeling data, not instruments (equipment) used. If you have any information about this, please share it here.
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You might be biased against measurements because you feel you cannot afford them. But often there are meteorological networks nearby - based on stations, weather radar, lidar, GPS dual frequency electron density, meteorological satellites, and many amateur networks. One measurement is sometimes worth 10 supercomputer's. You did not say what you are trying to do, or where. The location matters a lot - for the complexity of the modeled region, for the sparsity or abundance of continuous data stream, and for the possibility of others working on the same place.
I found that many of the seismic stations are recording meteorological data. Because when you work at parts per million or parts per billion problems the atmospheric variations are often one of the largest variations. Sometimes simple correlations remove or identify the the big variations. But I found that imaging arrays ultimately are needed.
I am sorry I cannot answer you more clearly. You don't say your restraints in terms of computing resources. If you have 10 supercomputer nodes, there are one set of options. If you have only a Raspberry Pi, then something else is needed.
I am sitting here listening to a lightning storm passing over the area. It reminds me of all the electromagnetic sensor methods for monitoring weather in 3D and quantitatively. You did not say how long your project related to the question might be. If it is a casual "I wonder?" or "a ten year plan", the methods are different.
I see you are working with geopotential. The daily variations of the gradient of the potential are easily measurable. After subtracting the sun moon portion of that, the largest component is the local atmosphere. I mentioned the seismic stations measuring temperature, pressure, humidity, acoustic. That is because the acceleration is correlated with atmospheric events and properties.
The most cost effective way to get good estimates for different locations is to use a combination of all the available continuous data streams and their correlations, then use algorithms that can run on low cost equipment. But all that is set by what you are trying to accomplish.
Atomic clocks are "direct geopotential sensors". You might want to look more closely at gravimeters and gravity gradiometers. Again, I cannot tell what you are trying to do, so I cannot be more specific. But generally the gravimeter networks are more sensitive to meteorological changes. I am trying to set up gravitational imaging arrays to 3D image the atmosphere for cities that also have 3D weather radar and climate models at sufficient resolution - for correlations. The less expensive gravitational sensors, once calibrated, are not bound by electromagnetic noise or weather conditions as much.
You seem to be assuming "I can get some data more easily by running a model". But often the best models are proprietary or horribly difficult to run. Then your best bet is to locate places on the Internet where the data is served continuously. The European Space Agency has a rather large project on global climate change that has to estimate global climate at any location over long time periods. Their model outputs are available. They keep moving things around, but you might try looking here - https://spacedata.copernicus.eu/ just to get some sense of what is going on. Brian Bramanto link is good. But the global climate model community is large and varied, and has many applications.
All their models, and any model you find will have to have been calibrated using real data, to be of any use. So whether you tap the raw data, or they do it and feed you the processed results - you are ultimately looking at measurements by someone. Usually many someones.
Looks like you and I are in the same project. You might want to take a closer look at Mossbauer methods for measuring the geopotential. That is the first absolute gravitational potential measurement. Also, the neutrino and cosmic ray networks are getting to the level of sensitivity and temporal resolution they can pick up daily and hourly variations driven by local pressure temperature humidity. Their results depend on the local atmospheric density.
Rather than TPH, you might want to think more in terms of mass density variations. PV = nRT is really very useful. n(i) = ParticlesPerCubicMeter(i) = MassDensity * AvagadrosNumber/ MolecularWeight(i) for sets of molecular and atomic species. i is the index for the species. It might seem trivial, but if you have to use it a million times and it gets embedded in thousands of different models, it is good to bring it out explicitly to be able to combine results from many groups.
Richard Collins, The Internet Foundation
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About GNSS ionospheric model
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Nequick topside model
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I want to log GPS/GNSS data on an iPhone/iPad and look for a dedicated app. I want to log as much data as possible (DOPS, satellite data [strength, number, position,...], used constellations, frequencies...) over a longer period of time. Additional data from other internal sensors (IMU) would also be ideal. The recording should not depend on the position change, ideally in NMEA or RAW and stored locally. Other data formats are also possible if they contain the necessary information.
Does anyone know such an app for IOS? I have tried dozens and have not found one that meets the requirements.
Thanks
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Thank you for your answer. The programme works smoothly, even in the combination of GNSS and other sensors. It is also available for iOS and Android. It still has one weakness. GPS/GNSS/Location alone provides the number of satellites, in combination with other sensors this number of satellites is missing. Nevertheless, I will use this app.
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What is the position error limit for GPS aided INS sensor fusion for small rockets?
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Dear Researchers
How can we connect an GNSS external antenna to mobile phones?
What GNSS antennas can we use for this?
I will be grateful for your answers.
MB
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Depends on what kind of phone you have. Many Android (older) Phones use U.FL connectors (https://en.wikipedia.org/wiki/Hirose_U.FL) . You can just disconnect the original antenna and replace it with the new one. On new ones you might have to solder a coax cable onto the PCB.
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Satellite Laser Ranging (SLR) and Global Navigation Satellite System (GNSS) both measure the ellipsoidal heights. Which measurement of ellipsoidal height is more accurate?
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In the ITRF2014, the vertical (height) components of coordinates are slightly better for GNSS than for SLR: ca. 5 or 6 mm vs. 8 mm WRMS averages, see Table 2 in Altamimi et al., ITRF2014: A new release of the International Terrestrial Reference Frame modeling nonlinear station motions, 2016. (The full text is freely available at http://onlinelibrary.wiley.com/doi/10.1002/2016JB013098/full and was also reproduced in IERS Technical No. 38 "Analysis and results of ITRF2014", available for download at https://www.iers.org/TN38.) However, these are mean values for permanent stations and long measurements. A short measurement of a single GNSS station will be considerably worse.
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Global Navigation Satellite System
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thanks Endeshaw for your information
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I mean besides the official interface control documents provided for GPS, Galileo, GLONASS, and BeiDou, is there a relatively recent document that lists the services broadcasted and the main signal characteristics (e.g. carrier, modulation, chiprate) at least for these global systems?
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Thank you very much
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can anyone give an article related to this question?
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This free eBook (100 pages) may be helpful for general questions on GNSS observations: http://arf.berkeley.edu/files/attachments/equipment/NovAtel-Intro-to-GNSS2015.pdf
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The L5 signals from GNSS (US GPS/NaVIC/GLONASS) are being explored for wide applications. With focus on assessing the errors in (GPS) location data, what are the fundamental steps involved in determining errors or corrections that are necessary. Key points on validation mechanism.
I am exploring this topic and it will great if specific literature on fundamentals corrections adopted on processing of L5 signals can be highlighted.
Thanks in advance.
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You can read this paper:
Testing GPS L5 Tracking Algorithms and their Impact on Positioning Accuracy
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I tried to compute IRIDIUM SV ECEF coordinates using standard IS-GPS-200D almanac procedure. I downloaded TLE file with IRIDIUM SVs parameters from Celestrak. I successfully managed to convert/compute almost all necessary data for the calculation from TLE. I miss only RoRAAN (OMEGA dot). Could you give me some advice? Is it derived from B* drag term? Thank you in advance.
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Thank you for the reply. Please excuse me the delay with response. I found your answer very helpful. I'm going to implement your code into my calculation. I will let you know about the result. Best regards, PSD
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Besides positioning solutions, Global Navigation Satellite Systems (GNSS) receivers can provide a reference clock signal known as Pulse-per-Second (PPS or 1-PPS). A TTL electrical signal that is used in several applications for synchronization purposes.
  1. Is the PPS physically generated through a digitally-controlled oscillator (or line driver) whose offset is periodically re-initialized by the estimated clock bias (retrieved by means of PVT algorithms)?
  2. Are there any specific filters/estimators devoted to a fine PPS generation and control?
  3. Does some colleague know any reference providing technical details on this aspect?
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we worked on the design and implementation of of a GPS receiver for the sake of extracting the one PPS, we could realize the signal acquisition phase and the tracking phase where we could generate a copy of the carrier with reduced frequency and of the pn conde clock generator. BY dividing these signal with appropriate division ratio one can get the one PPS. Its stability was to be evaluated. But the last divider stage is not yet realized and we plan to realize it and after that evaluate its accuracy and stability. please see the papers:
Once achieved I will notify you.
Best wishes
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My research is related to the Ionospheric disturbances for an earthquake, and the point of my question is after I calculated and plotted the Ionospheric Pierce Point (IPP) & Sub-Ionospheric Point (SIP) trajectories, and the values of STEC and their anomalies from the closest satellite to the epicenter of an earthquake area by using several observation stations from sugar, I stopped on the step of calculating or plotting the STEC & VTEC for all my GPS stations because I don't know even I don't have the Matlab script for it. (please provide me a full Matlab script for it) with thanks
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The subframe parameters are mentioned along with scaling factors in the ICD. How to use them while extracting navigation parameters from binary data?
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Convert the binary number to decimal and multiply with the scaling factor to get the proper value.
If the data is in 2's complement format, then Abdul Malik Khan Abdul Malik Khan convert q number to decimal and multiply the scaling factor.
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I was looking into GNSS derived TEC data and most of the data were missing and repeatedly occuring. What is the most precise way to handle those missing data? I guess interpolation is not good enough to perform for a large number of missing data.
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There are a lot of websites with GNSS data,
It is better to select periods with good continuous data sets
sincerely
Christine
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I want to compare two TEC models. Except the comparison of diurnal vTEC, I want to analyze deviation in mean monthly vTEC by taking single airthematic average for whole month. While doing so, I am averaging quiet day as well as disturbed day TEC. But my study is not adressing the performance of models in disturbed or quiet day. Study is focused on overall performance. So, what I believe is if two models are predicting TEC of same location then both should give the similar average for the month. But I want to confirm, wheather other statistical factor effects the value while mixing quiet day and disturbed day TEC or not?? Is this concept significant in comparing two TEC models?
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In my opinion, it's better to distinguish the study into disturbed and quiet period to validate the performance of the model. This is because, the average value of the entire month sometime fails to address the storm effect on the vTEC. By dividing the study into two separate categories, we will have better overview of their overall performance.
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I need information on the power of the transmitting antennas of the GNSS satellites and the signals they transmit. Is there an official&technical report, data set or published research article on this?
I would be very grateful for your help.
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The explanation of your question here may not be enough, but I have had studies in this field and I suggest the following articles to you. I hope they help.
  • 10.1007/s00190-017-1082-2
  • 10.1155/2016/2154763
  • 10.1007/s00190-017-1082-2
  • 10.3390/data5010018
Wishing you the best on your way.
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I am interested in the changes in the vibration response of a long-span bridge structure before and after damage. I am developing a dynamic characteristic identification method, which is tested only with simulated data. It will be very helpful with the actual dynamic deformation data to verify this method' capcity of identifying the changes in the characteristics such as the frequency extracted from the monitoring series before and after the structure's damaged.
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If you can send me some relevant GNSS monitoring data , you will be gratefully acknowledged in my future publications.
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I am researching a method to speed up the GPS acquisition in cold start. Rather than an exhaustive search on all satellites, I observed that the satellite distribution can give some information to reduce the number of searches.
For example, if I can find the first satellite with Doppler value. I think there exists some way to calculate the probability of detection of other satellites.
Could you recommend some references to start looking at?
Thank you.
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As soon as the receiver identifies the satellites using Doppler values, then that will no longer be the cold start but rather the warm start. At this stage, the receiver uses the recent almanac in memory to map the satellites and their Doppler offsets. Thus, what is necessary is only to check the anticipated pseudorandom noise (PRN) codes at the expected Doppler offsets. Henceforth, searching the sky becomes worthless.
How can we determine the satellite during cold start?
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Other than using the Doppler values, the positions of the other satellites may be detected using the orbital data from the almanac. In any given constellation, each satellite transmits orbital parameters for all satellites alongside auxiliary health and status information. Since the ephemeris data is transmitted only for each individual satellite, then you may simply compute the satellite positions using the orbital equations at any given point in time.
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Apart from that, you may get the ephemeris and clock information from the cellphone link rather than through the satellite link, a concept which may be termed as assisted satellite positioning. The strength of this approach is that the amount of time required to get all the critical information shortened.
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While the orbit design has something to do with the overall satellite configuration, the receiver architecture has a vital role in the task of identifying the satellites in order to calculate its own 3D position and clock offset, on the other hand. Therefore, the overall cold start searching time may improve with multi-corellator and high-sensitivity Global Navigation Satellite System (GNSS) receivers.
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In the U.S., Executive Order 13905( Federal Register : Strengthening National Resilience Through Responsible Use of Positioning, Navigation, and Timing Services) signed 02-12-2020, ordered several federal agencies to conduct vulnerability assessments related to critical infrastructure. I'm looking for qualified opinions / research on the potential for degradation or loss of access to GPS / GNSS to potentially impact critical infrastructure at hydro-electric dams.
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Well, 'Yes'. And not just the obvious spatial difficulties, it is the reliance on timing signals. The epicenter is NIST: Overview at https://www.nist.gov/news-events/news/2021/02/nist-finalizes-cybersecurity-guidance-positioning-navigation-and-timing and from there are other domain specific documents like https://www.nist.gov/news-events/news/2019/08/situational-awareness-electric-utilities-nist-publishes-cybersecurity
Behind all these is usually quite a paper trail of conference presentations, meeting transcripts, etc. from stakeholders providing input, usually referenced in the bibliographies of the documents. The exceptions are, obviously, classified content with specifics on actual incidents and unresolved current vulnerabilities.
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In the relativistic theory for synchronization between satellite and ground atomic clocks, the major sources of relativistic effects are relative motion between the two clocks and the movement of clocks in a gravitational potential.
I am looking for the recent research and adapted clock correction models that have been modified on this topic as well as what are factors must be considered when comparing the proper/coordinate time of a clock at rest on the geoid and a clock in Earth orbit satellite?
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When they first sent up GPS satellites, they programmed them with what they believed to be the correct relativistic changes that would be needed which would affect GPS location determinations. They also installed a programmable system within these satellites that can be reprogrammed from the ground, and they could upload any changes when the satellite was overhead.
What they found was that the relativity program the system was given was not accurate enough for GPS system calculations. They tried to correct these equations and related program for a period of time but finally gave up. Instead they uploaded a programmed algorithm that they believed could make the necessary corrections based upon information from the ground coming from one or more additional GPS satellites. The new system worked. So now all relativity corrections of GPS satellites are now based upon a self-correcting algorithm using new information from the ground and other GPS satellites on an ongoing basis.
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Different Global Navigation Satellite Systems are vulnerable to different kinds of intereferne, some are intentional while others are unintentional. Jamming and spoofing are 2 types of intentional intereferne that affect the accuracy of a GNSS or RNSS measurements
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I think in order to cancel the intercept signal you have to detect it and that what you want to realize by your software defined radio. So need a software defined radio developing kit that work in the frequency band of the global position systems. You may use the national instrument software defined radio kits which are based on Ettus kits.
Here I would like to pay your attention that the GPS signals are spread spectrum signals which are primarily more immune against narrow band jamming.
So, may not need extra precautions against the interference.
One must study how far these signals are immune against jamming.
I would like that you refer to the paper in the link which deals with generations
and
Best wishes
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I am working on a GNSS/INS tight integration model for vehicle localization during loss of GNSS such as under parking, dense trees etc. using IMU measurements only with the positioning error less than 2 meters for at least 1 minute. However, positioning error is quickly increasing in the absence of GNSS as well as velocity error. I am trying to adopt NHC (non-holonomic constraint) model along IMU measurements. However, accuracy is not much improved. I studied several papers related to NHC model and theoretically NHC model should work. Can anyone guide me to integrate NHC model and IMU especially in the real time implementation perspective in the NED/ECEF frame of reference. Thanks in advance.
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Based on my experiences on implementing NHC on real products, there are some challenges:
1 - Misalignment between vehicle body frame and IMU frame may be estimated, you can detect it when plotting the signals in the rear-wheel frame.
2 - If the vehicle turns drastically or jumps, NHC should be deactive.
3 - The measurement noise covariance matrix for NHC should be adaptively tuned.
You can have a look at Groves's book Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems.
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Recently I have some ideas and wanna do some research on the building/bridge deformation monitoring. However, I don't have the data right now. Can anyone provide the data? Much thanks!
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Depends on your study area. Local bodies and organisations sometimes observe these values and most often they are happy to share it for research work.
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I know the tight integration improves the performance of GNSS receiver in terms of position, velocity and attitude. Normally, we assume that tight integration can handle the short term loss of GNSS signals. However, for a moving vehicle where attitude is quickly changing, loss of GNSS results in accumulation of position and velocity error. Can we model the attitude/ heading change to reduce the accumulated error ?
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For such kind of implementations, a CORS network with RTK may probably works better.
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Does anyone working in the field of GNSS multi-agent/multi-receiver positioning know public data repositories including high-rate positioning data (> 10 Hz PVT solutions)?
Urban or mild-urban track logs obtained through high-accuracy GNSS/INS/RTK receivers are valuable options (sub-meter accuracy).
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Perhaps you could consider the IGS MGEX products. This RINEX files mostly contain data from all GNSSs.
Good luck!
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I'd like to use the VADASE approach for Hungarian GNSS observations in RINEX format wrt to the Zagreb earthquake in 2020. It would be a great help if you had any software tools available for use. I'm looking forward to your answer!
Thank you in advance!
BEst regards,
Szabolcs Rozsa
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I've read several articles and the issue is not clear. Some articles establish that even at LEO altitudes, the radiation pressure plays the dominant role. However, other articles affirm that the most important phenomena affecting satellite orbits (besides gravity) is the atmospheric drag.
After reading all this information, I've come to the conclusion that at around 850 km the radiation pressure begins to play the dominant role. Is this correct?
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It depends on multiple factors and some of which dominate only specific altitude which unfortunately make it very complex do not forget the geometry as well but this graph should be a good approximation.
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The web-based online PPP processing services (e.g. AUSPOS) have ITRF2014 output (not the WGS84 output). Thanks!
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There is no need to transform the ITRF2014 coordinates. "ITRF20014, ITRF2008 and WGS84 (G1674) are likely to agree at the centimeter level", see https://confluence.qps.nl/qinsy/latest/en/international-terrestrial-reference-frame-2014-itrf2014-182618383.html .
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i want to prospect ground water in rocky terrain using satellite imagery. i need to know the most suitable data to be use, the method of extraction and the procedure for achieving it. Thank you in anticipation of your useful contribution.
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For automatic lineament extraction, you can achieve this by applying a combination of the following softwares: Arcmap 10.0+, ENVI 5.1, PCI GEOMATICA 2016, ROCKWORKS 16.
STEP1: Use ENVI software to perform principal component analysis (PCA) on the spectral image band of Landsat8.
STEP2: GEOMATICA is used to perform an automatic lineament delineation from the PC1.tiff generated from ENVI. This is done with the aid of lineament extraction algorithm in the Tool from toolbar
STEP3: ARCMAP is used for handling extracted lineament (splitting compound line into simple lines, editing lineament attribute, exporting lineament as cad file
STEP4: ROCKWORKS is used to process the exported lineament Cad file to determine the trend of the lineament and hence generating rose diagram.
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I did some experiments in Indonesia. Nowadays RTK GNSS receivers seem to work better when under vegetation canopy (fixing ratio more than 90%). Is this real, or just a system tweak?
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The improvement is mainly because of large number of GNSS satellites above the receiver (GNSS) at any given point of time. This primarily improve the error adjustments and thus increase the accuracy. However, the issues under canopy still remains to some extent depending on its density.
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Elevations in S0 Terrengmodell Svalbard (dataset by Norwegian Polar Institute, 10.21334/npolar.2014.dce53a47) are above sea level. I have some GNSS measurements above WGS84 ellipsoid and want to compare them with S0 DTM, hence I need to know the conversion from original above-sea-level altitudes to WGS84 elevations. I am not sure what conversion was used to construct S0 Terrengmodell - was it one of global geoid models (EGM96, maybe?) or some local height system corrections. I can't find any data myself (in Eglish at least). Does anybody know this technical details?
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as Elevations in S0 Terrengmodell based on mean sea level or the geoid, and since WGS84 ellepsoidal heights were based on the ellepsoid surface, you have to know the geoid height (i.e the difference between the ellepsoid surface and the surface of the geoid - mean sea level surface) to convert the ellepsoidal heights to mean sea level heights which are comparable with the S0 DTM.
For accurate conversion ask for the Norwegian geoid model for the area under consideration, otherwise you can get the estimated geoid from the EGM2008 global geoid model.
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I am working on some research related to the enhancement of smartphone positioning technologies. I am curious about the format of the GNSS data stream from GNSS chipset on smartphone. I've been researching on the use of external GNSS receiver to enhance the positioning of smartphone users e.g using GNSS module from u-blox, skytraq etc.
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1. Suggestion: Why you are using external receiver/s to improve the positioning, I mean you can use built-in system to improve the solution. contact me for further help.
2. In your case, use Matlab, goGPS, GoogleEarthPro, GPS Track Editor, SBG Center or any other related live simulations where you can see each and every details you required.
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Hello,
I saw that in the rinex format there is a transmission time for the broadcast ephemeris. 
 I was wondering where in the nav message (i.e. which subframe/word number) is the transmission time being transmitted?
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I believe this is when this particular ephemeris dataset is either first broadcast or first received by a ground receiver.
For GPS this is roughly 2-hours before the Toe
For GLONASS this is roughly 15-minutes before Toe
For Galileo, it's a bit puzzling that the transmission time is like 11-minutes or so after Toe. Does anyone know why?
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I'm looking for information on the size of the global satellite industry - both commercial and whatever information is available on government. I'd like to know more about the number of satellites in the various orbits, number of geosynchronous satellites, construction and launch cost data, and potential future uses.
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Euroconsult's report
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I am using a SPIRENT simulator to generate GNSS and WASS signals. I am receiving the RF signal on a NovAtel receiver. The NovAtel connect software shows that the WAAS signals are available but it indicates that “the WASS signals are not used in the solution”, Any one can help?
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First, is the receiver authorized for WAAS? You have to purchase that option and have it enabled on the receiver with the auth code. Assuming that you have a WAAS enabled receiver use the following commands for WAAS:
psrdiffsource sbas
sbascontrol enable waas
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Hello Everyone,
I have a very basic question regarding BPSK modulation.
I am working on GNSS signals, and I came across BPSK(5) modulation scheme. But I don't know that what this "5" means?
As per my understanding, this only tells about the chipping rate of the modulating signal. which is 1.023Msps in BPSK(1), and here it is BPSK(5), so it means that the chipping rate would be 5*1.023Msps.
Can someone please make it clear for me that my understanding is correct OR is there something else that I am not getting?
Thank you
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Hi,
Yes it's exctly that ! The numbre inside the bracket is in reference of the GPS spreading code frequency, 1.032MHz.
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I want to know if it is possible to estimate coefficients of Marini-Murray mapping function from GNSS data in PPP processing. Or there will be a strong correlation with ZTD?
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of course*
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I am trying to use GAMP (GNSS Analysis software for Multi-constellation and multi-frequency Precise positioning) in my research, and I have a question.
How can I obtain single solution for ppp_static mode?
In other word, I want the final coordinates of the station instead of all epochs coordinates.
Attached configure file and position file.
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Interpreting your output file in matrix form, here is the description for the columns:
  1. Column 1: 4-digit year
  2. Column 2: month
  3. Column 3: day
  4. Column 4: hour
  5. Column 5: minute
  6. Column 6: second
  7. Column 7: GPS week
  8. Column 8: GPS seconds of week
  9. Column 9: East-coordinate
  10. Column 10: North-coordinate
  11. Column 11: Up-coordinate
  12. The associated errors are contained in 12th, 13th ...and nth column. These are provided with respect to epoch in your output file.
  13. You can get the mean of 12th, 13th and 14th column to obtain errors in East, North and Up components.
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In the Global Navigation Satellite System (GNSS) online processing services, there are two algorithms for the solution: Double Difference (DD) and Precise Point Positioning (PPP).
My question: which one gives a precise solution in the following time periods:
1- At the duration between (1 - 3 hours).
2- At the duration more than 10 hours.
Thanks for your Interest...
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You're welcome Mourtadha Sarhan Sachit ,
I'm pretty sure DD will achieve better results than PPP.
Generally each country has its densified network of continuous GNSS tracking stations with adjusted coordinates (or known coordinates), i.e., an official geodetic reference system.
IGS network stations are really scarce, when you want to work with a short baseline and reduce tracking time.
One suggestion is to track a vertex (Base) for a longer time (for example, 4 hours) and simultaneously track other vertices for 15 min (Semi kinematic Method - Stop and Go), with baselines smaller than 20 km. With this method you can achieve accuracy better of a few centimeters.
If the Base has known coordinates, then you can apply directly the DD method, but if it is not known (which happens in most cases), you should perform static relative processing with the closest stations of the geodetic network in your region.
It's a little complicated to explain everything with a few words, but I hope you have understood the main idea.
I suggest consulting the following book:
Satellite Geodesy, 2nd Ed. Günter Seeber
It covers very well all these methods of positioning.
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Presently, I am determining local geoid model of an area using the gravimetric-geometric method and I am sensing that there would be large differences between the known orthometric heights of selected points and the orthometric heights of the same points obtained from the local geoid model, someone should please tell me what to do in such situation.
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Dear Okiemute,
I agree with Dr. Ruby. Just want to add, go for 7-parameter model to account for bias and tilts in the geometric and gravimetric values. It presents better results as compared to 4-paramter model.
Regards,
Ropesh Goyal
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VTEC data calculated from GNSS observations, need to plot it over a regional area but the format as ionex file and calculated within 15min /day
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Dear Mohamed Freeshah,
you could try my Python script (https://github.com/Albom/GNSS_utils/blob/master/test_ionex.py). It produces output data in gnuplot data format. It also possible to plot world map on the same plot.
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Ussually, we use running average to detrend total electron content (TEC) data from GPS(GNSS) and to filter required period range. Could someone recomend a paper devoted to comparison of different filters for this purpose.
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Dear Yury,
Check out this paper...
"Identification of vertical total electron content by time series analysis, Digital Signal Processing 19(4):740-749, 2009 by Erdogan H and Arslan N."
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How to calculate Ionospheric Pierce Point value from azhimut and elevation angles for a dual frequency GNSS data?
I would like to work out the height of maximum electron density of ionosphere.
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You can use the papers previouly cited together with Lat and Long of the location of the receiver. But for such calculation, there is no need of a dual frequncy dara!
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Regularly, geodesists at international colloquium wonder what is the next big step in geodesy (see Geodesy and its future, A. Dermanis & F. Sanso /the role of geodesy – C. Rizos – FIG 2012). If we exclude engineering applications associated with the rise of GNSS and all the new constellations (GLONASS, Beidou, Gallileo,…) which will indubitably promote new technological niches in the Location Based Services market beyond navigation and tracking applications.
We are then left with the applications of geodesy to geosciences a.k.a environmental geodesy- e.g. . the study of reference frame in geophysics with plate tectonics movement & earth rotation; oceanography with multiple applications including the measurements of tides, height datum and bathymetry; in climate change – geodesists estimate the sea-level rise around the world. Nowadays, geodesists need to analyse different satellite missions (GNSS, GRACE, satellite altimetry …) and correlate various observations in order to produce robust models and describe/discover new natural phenomena. Thus, does the future of environmental geodesy rely on AI and big data algorithms to process & analyse large amount of data and build empirical models used in the analysis/prediction of natural phenomena? With the need to monitor closely climate change, geodesists will be involved in studies involving the data analysis of future satellite missions (see my previous question on “big data and climate change”).
Last but not least, with the willingness of exploring Mars and other planets, a future field of interest may be the application of geodesy in the analysis of geophysical phenomena occurring on those planets…. What do you think?
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alright. All clear. Thanks for sharing.
Best Wishes, Jean-Philippe
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Hello,
Let us assume we have a cellular antenna. I consider the frequency 800 MHz. I want to co-locate next to my antenna GNSS and SDARS antennas. The 2nd and 3rd harmonics of 800 MHz fall in the L1 band of GPS and SDARS range, respectively. What considerations must be taken regarding the isolation between antennas? is it enough to have a large isolation, or would I need ,too, to have a strong attenuation at the 1600 and 2400 MHz?
Thank you1
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Montaha,
Adding to the colleagues above, i would like to comment your question from the fundamental point of view. You have three antennas which lay near to each other,
One transmit antennas and two receiving antennas. Every antenna has its own port to connect it to its rf front end. Assume this ports are P1,P2,and P3, respectively.
If the antennas are couples you can measure the coupling between them by the transmission coefficients S21,and S31 with anrtenna 1 is the transmitting antenna. In order to measure how far the antennas are isolated from each other you have to measure S21 and S31 at the intended frequency.
As isolation between antennas increase S21 and S31 will get smaller. For complete isolation S21 and S31 will be zero and the attenuation will be infinity.
So, things are put in its context.
Best wishes
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It's true that elevation from GPS receivers are measured from the ellipsoid as a reference rather than the geiod/mean sea level (MSL). This topic is a little trick though.
But my question is whether there are specialized GPS receivers that are capable of doing the conversion from ellipsoid to orthormetric and hence output othormetric elevation. Or is there any way any GPS receiver can be tweaked to do this calculation automatically?
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GPS/GNSS receivers do not give orthometric heights, they only give ellipsoidal heights. This is because, the heights are geometric as they are computed with respect to the ellipsoid. Orthometric heights are obtained with respect to the geoid/MSL. Orthometric heights can only be obtained from processed GPS/GNSS observations if the local geoid model of the area of observation is applied.
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Hi,
working with extended and unscented Kalman filter brings me to the question, how I can compare them in simulations as fair as possible.
My first intent was to choose the process noise matrix Q and measurement noise matrix R for both filters in the same way.
I found out, that my UKF works much better for 10*R, while the EKF is more accurate for 1*R. I do offline simulations for a navigation problem, using measured IMU and GNSS data.
My feelings says me, that even for same noise matrices, the comparison is not as easy as I thought, because of the sigma points building procedure and so on...
I found that paper:
which says that EKF can perform better covariance estimations in certain regions (higher mean estimates).
Has somebody some tips for me, regarding that topic?
Best regards,
Max
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For nonlinear estimation, both the EKF and the UKF are approximate strategies. The propagation of the error covariance matrix P is simplified by the use of Jacobian in the EKF and the choice of sigma points in the UKF.
Though Q and R matrices generally refer to the process noise covariance and measurement noise covariance respectively, they can also compensate for the errors in the approximation of the propagation of the error covariance P. That is, in the EKF Q can be tuned such that it compensates for the loss of higher order information that result from linearization. The same holds for the UKF too.
To sum up, Q and R can be tuned to represent a little more than process noise and measurement noise for nonlinear Kalman-based estimation schemes. This gives rise to difficulty in tuning for some applications. Since you work with simulated data, you can easily verify if your tuning is reasonably correct by checking if the actual error covariance is approximately close to the one obtained by the filter. This implies that the estimation scheme works reasonably well. In the absence of the true state value as happens in real-world situations, the innovations can be compared.
Coming to the specific case, if you want to do the fair comparison tune both the estimation schemes separately to obtain the best results. Then compare them as pointed out early.
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Dear all
if I have the SD carrier-phase measurements how can I compute the SD residuals? Do i need to calculate the SD residuals before fixing the integer ambiguity?
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you can compute the SD as
SD = PR - Range
Where PR is measure psuedorange and range can be calculated through distance equation, using own and satellite position.
In ground based systems, survey techniques are utilized to find the own position, which is a preferred method. However in dynamic situations, the measured position can be used as own position. Using measured position in SD is not suitable for finding the error corrections, but could use for integrity calculations.
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Automatic Dependent Surveillance Broadcast (ADS-B) is a key avionics technology used for aviation cooperative surveillance (i.e., aircraft separation assurance and collision avoidance). However, the absence of adequate security features makes this system vulnerable to a number of cyber-physical threats (jamming, spoofing, meaconing, etc.). What technological solutions can be introduced to address this challenge?
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Dear Charles,
Thank you very much for your message and for the valuable documents. I am also very actively involved in this line of research. A recent paper on GNSS performance threats and augmentation strategies in aviation was recently published in JPAS (for convenience, the link is provided below):
In addition to addressing GNSS issues, it would be nice working together and investigating the feasibility of specific safety features that could be included in the ADS-B data-link as well.
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I am working on GNSS signal L5 band. I want to obtain the I/Q signal from it with a PXIe-5624R IF Digitizer. Does the sampling frequency is enough for that application ?
Moreover, does someone have some exemple of the implementation of the PXIE-5624R in Labview environnement ? No one are provided by NI...
Great Regards
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Direct sampling of RF signal requires a notch filter at front-end to reject signal in other bands, otherwise all unwanted signals will also get sampled.
2GS/s is more than enough for working on L5.
The advantage of Direct sampling is that you do not need down conversion, but the requirement of notch filter is too stringent that it is impossible to be realized.
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To get the STEC i want IONEX file of IRNSS data. Any way to get it ?
is it possible to extract the STEC from RINEX file ?
Any suggestions ?
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IRNSS RINEX files provides you raw measurements (observation file), satellite ephemeris (nav files). They do not have slant TEC values, you will need to compute them from these measurements.
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I have 24 hours dual frequency GPS observations of 10 points 
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Just a quick update: The Bern server has been changed to a new host name. The CODE maps can now be retrieved from here: ftp://ftp.aiub.unibe.ch/CODE/
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Anyone out there, please help me with this. I can't understand what vertical delay values are used here and how to put that in the matrix ?
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thank you so much sir
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I never use Bernese to process GNSS data before
Is there anyone can help me?
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