Skip to main content

A GNSS reflectometry software package

Project description

News

The code now checks to see if you have installed fortran translators. If you haven't, it uses python to translate the RINEX file. SO while the default is still assuming you are using fortran, it is not a deal breaker.

I have started putting together a set of use cases.

CDDIS is an important GNSS data archive. Because of the way that CDDIS has implemented security restrictions, we have had to change our download access. For this reason we strongly urge that you install wget on your machine and that it live in your path. You will only have very limited analysis abilities without it.

I have added more defaults so you don't have to make so many decisions. The defaults are that
you are using GPS receiver (not GNSS) and have a fairly standard geodetic site (i.e. not super tall, < 5 meters). If you have previously used this package, please note these changes to rinex2snr, quickLook, and gnssir. Optional commandline inputs are still allowed.

How can you learn how to run this code correctly? You should start by reading Roesler and Larson, 2018. Although this article was originally written to accompany Matlab scripts, the principles are the same. It explains to you what a reflection zone means and what a Nyquist frequency is for GNSS reflections. My reflection zone webapp will help you pick appropriate elevation and azimuth angles.

If you are interested in measuring sea level, this webapp tells you how high your site is above sea level.

Philosophical Statement

In geodesy, you don't really need to know much about what you are doing to calculate a reasonably precise position from GPS data. That's just the way it is. (Note: that is also thanks to the hard work of the geodesists that wrote the computer codes). For GPS/GNSS reflections, you need to know a little bit more - like what are you trying to do? Are you trying to measure water levels? Then you need to know where the water is! (with respect to your antenna, i.e. which azimuths are good and which are bad). Another application of this code is to measure snow accumulation. If you have a bunch of obstructions near your antenna, you are responsible for knowing not to use that region. If your antenna is 10 meters above the reflection area, and the software default only computes answers up to 6 meters, the code will not tell you anything useful. It is up to you to know what is best for the site and modify the inputs accordingly. I encourage you to get to know your site. If it belongs to you, look at photographs. If you can't find photographs, use Google Earth.

gnssrefl

gnssrefl is a new version of my GNSS interferometric reflectometry (GNSS-IR) code.

The main difference bewteen this version and previous versions is that I am attempting to use proper python packaging rules!. I have separated out the main parts of the code and the command line inputs so that you can use the gnssrefl libraries yourself or do it all from the command line. This should also - hopefully - make it easier for the production of Jupyter notebooks. The latter are to be developed by UNAVCO with NASA GNSS Science Team funding.

If you would like to try out reflectometry without installing the code

I recommend you use the web app I developed. It can show you representative results with minimal constraints. It should provide results in less than 10 seconds.

If you prefer Matlab

I had a working matlab version on github, but I will not be updating it. You will very likely have to make changes to accommodate the recent change in security protocols at CDDIS.

Overview Comments

The goal of this python repository is to help you compute (and evaluate) GNSS-based reflectometry parameters using geodetic data. This method is often called GNSS-IR, or GNSS Interferometric Reflectometry. There are three main modules:

  • rinex2snr translates RINEX files into SNR files needed for analysis.

  • gnssir computes reflector heights (RH) from SNR files.

  • quickLook gives you a quick (visual) assessment of a file without dealing with the details associated with gnssir. It is not meant to be used for routine analysis.

There are also various utilities you might find to be useful (see the last section).

The rest of this README file is about how to install and run the code. It is not a class about GNSS interferometric reflectometry. If you are unsure about why various restrictions are being applied, you really need to read Roesler and Larson (2018) and similar. I am committed in principle to set up some online courses to teach people about GNSS reflections, but funding for these courses is not in hand at the moment.

To summarize, direct (blue) and reflected (red) GNSS signals interfere and create an interference pattern that can be observed in GNSS data as a satellite rises or sets. The frequency of this interference pattern is directly related to the height of the antenna phase center above the reflecting surface, or reflector height RH (purple). Accordingly, this code strips out rising and setting satellite arcs and estimates RH.

Environment Variables

You should define three environment variables:

  • EXE = where various RINEX executables will live.

  • ORBITS = where the GPS/GNSS orbits will be stored. They will be listed under directories by year and sp3 or nav depending on the orbit format.

  • REFL_CODE = where the reflection code inputs (SNR files and instructions) and outputs (RH) will be stored (see below). Both SNR files and results will be saved here in year subdirectories.

If you don't define these environment variables, the code should assume your local working directory (where you installed the code) is where you want everything to be. The orbits, SNR files, and periodogram results are stored in directories in year, followed by type, i.e. snr, results, sp3, nav, and then by station name.

Python

If you are using the version from gitHub:

If you use the PyPi version:

  • make a directory, cd into that directory, set up a virtual environment
  • activate the virtual environment
  • pip install gnssrefl

To use only python codes, you will need to be sure that your RINEX files are uncompressed (i.e. not using Hatanaka compression, which end in a d instead of an o). Since many archives use Hatanaka compression, this will significantly limit what you can do. The second thing to know is that you should use the -fortran False flag when you make SNR files because the default behavior is to assume you are using fortran translators (gnssSNR.e or gpsSNR.e). Finally, you will not be able to use RINEX 3 files because I rely on the gfzrnx RINEX3 to RINEX2 translator.

Non-Python Code

All executables should be stored in the EXE directory. If you do not define EXE, it will look for them in your local working directory. The Fortran translators are much faster than using python. But if you don't want to use them, they are optional, that's fine. FYI, the python version is slow not because of the RINEX - it is because you need to calculate a crude model for satellite coordinates in this code. And that takes cpu time....

rinex2snr - making SNR files from RINEX files

The international standard for sharing GNSS data is called the RINEX format. A RINEX file has extraneous information in it (which we want to throw out) - and it does not provide some of the information needed for reflectometry (e.g. elevation and azimuth angles). The first task you have in GNSS-IR is to translate from RINEX into what I will call the SNR format. The latter will include azimuth and elevation angles. For the latter you will need an orbit file. rinex2snr will go get an orbit file for you. You can override the default orbit choice by selections given below.

There is no reason to save ALL the RINEX data as the reflections are only useful at the lower elevation angles. The default is to save all data with elevation lower than 30 degrees (this is called SNR format 66). Another SNR choice is 99, which saves elevation angle data between 5 and 30.

There are rules for naming RINEX files. My code requires that RINEX (version 2) files be lowercase. The filename must be 12 characters long (ssssddd0.yyo), where ssss is station name, ddd is day of year, followed by a zero, yy is the two character year and o stands for observation. If you have installed the CRX2RNX code, you can also provide a compressed RINEX format file, which ends in a d. I think my code allows you to gzip the RINEX files if you are providing them.

You can run rinex2snr at the command line. You required inputs are:

  • station name
  • year
  • day of year

If you installed the fortran translator gpsSNR.e, a sample call for a station called p041, restricted to GPS satellites, on day of year 132 and year 2020 would be:

rinex2snr p041 2020 132

If the RINEX file for p041 is in your local directory, it will translate it. If not, it will check four archives (unavco, sopac, cddis, and sonel) to find it. If you did not install a fortran translator, the command would be:

rinex2snr p041 2020 132 -fortran False

Here is an example from a site in Greenland (the RINEX file will be picked up from unavco):

rinex2snr gls1 2011 271

The code will also search ga (geoscience Australia), nz (New Zealand), ngs, and bkg if you invoke -archive, e.g.

rinex2snr tgho 2020 132 -archive nz

What if you want to run the code for all the data for a given year? This command analyzes all the data from the year 2019.

rinex2snr tgho 2019 1 -archive nz -doy_end 365

If your station name has 9 characters (lower case please), the code assumes you are looking for a RINEX 3 file. However, my code will store the SNR data using the normal 4 character name. You must install the gfzrnx executable that translates RINEX 3 to 2 to use RINEX 3 files in my code. rinex2snr currently only looks for RINEX 3 files at CDDIS (30 sec) and UNAVCO (15 sec). There are more archive options in download_rinex and someday I will merge these. If you do have your own RINEX 3 files, I use the community standard, that is upper case except for the extension (which is rnx). I know, it is weird.

Here are some examples for RINEX 3 conversions:

rinex2snr onsa00swe 2020 298

rinex2snr at0100usa 2020 55

rinex2snr mdo100usa 2020 290

rinex2snr mkea00usa 2020 290

The snr options are mostly based on the need to remove the "direct" signal. This is not related to a specific site mask and that is why the most frequently used options (99 and 66) have a maximum elevation angle of 30 degrees. The azimuth-specific mask is decided later when you need to run gnssir. The SNR choices are:

  • 66 is elevation angles less than 30 degrees (this is the default)
  • 99 is elevation angles of 5-30 degrees
  • 88 is elevation angles of 5-90 degrees
  • 50 is elevation angles less than 10 degrees (good for very tall sites, high-rate applications)

orbit file options for general users:

  • gps : will use GPS broadcast orbits (this is the default)
  • gps+glos : will use JAXA orbits which have GPS and Glonass (usually available in 48 hours)
  • gnss : will use GFZ orbits, which is multi-GNSS (available in 3-4 days?)

orbit file options for experts:

  • nav : GPS broadcast, perfectly adequate for reflectometry.
  • igs : IGS precise, GPS only
  • igr : IGS rapid, GPS only
  • jax : JAXA, GPS + Glonass, within a few days, very reliable
  • gbm : GFZ Potsdam, multi-GNSS, not rapid
  • grg: French group, GPS, Galileo and Glonass, not rapid
  • wum : Wuhan, multi-GNSS, not rapid

Other questions:

  • What if you do not want to install the fortran translators? Use -fortran False on the command line.

  • What if you are providing the RINEX files and you don't want the code to search for the files online? Use -nolook True

There is a rate command line input that has two values, high or low. However, if you invoke high, it currently only looks at the UNAVCO, GA, or NRCAN archives. Please beware - it takes a long time to download a highrate GNSS RINEX file (even when it is compressed). And it also takes a long time to compute orbits for it (and thus create a SNR file). If you did not install the Fortan RINEX translators, it takes a very, very, long time.

quickLook

Before using the gnssir code, I recommend you try quickLook. This allows you to quickly test various options (elevation angles, frequencies, azimuths). The required inputs are station name, year, and doy of year. You must have previously translated a RINEX file using rinex2snr for this to work.

quickLook has stored defaults for analyzing the spectral characteristics of the SNR data. In general these defaults are meant to facilitate users where the antenna is less than 5 meters tall.** If your site is taller than that, you will need to override the defaults. Similarly, the default elevation angles are 5-25 degrees. If that mask includes a reflection region you don't want to use, you need to override them.

For more information, use quickLook -h

Going back to our rinex2snr example, try running the data for station p041.

quickLook p041 2020 132

That command will produce this periodogram summary. By default, these are L1 data only. Note that the x-axis does not go beyond 6 meters. This is because you have used the defaults. Furthermore, note that results on the x-axis begin at 0.5 meters. Since you are not able to resolve very small reflector heights with this method, this region is not allowed. These periodograms give you a sense of whether there is a planar reflector below your antenna. The fact that the peaks in the periodograms bunch up around 2 meters means that at this site the antenna phase center is ~ 2 meters above the ground. The colors change as you try different satellites. If the data are plotted in gray that means you have a failed reflection. The quadrants are Northwest, Northeast and so on.

If you want to look at L2C data, try this by invoking -fr 20. In general, the results will be cleaner than L1 data (frequency number 1 in my code). The defaults reflector heights will not go beyond 6 meters. If you had set -h2 20, it would look like this. You aren't gaining anything by doing this.

Now look at the Greenland SNR file you created in the previous section.

quickLook gls1 2011 271

The periodogram peaks bunch up at a larger value, which just means the antenna was further from the planar reflector, which in this case is ice.

Finally, what do you do if your reflections site is taller than the default value of 6 meters? Does the code figure this out for you automatically? No, it does not. A short example: Make a SNR file using the defaults: rinex2snr smm3 2018 271 Now run quickLook using the defaults quickLook smm3 2018 271. Everything is gray (which means it didn't find a significant reflector) because you only calculated periodograms for height values of 0.5 to 6 meters. The site is ~16 meters above the ice. Accordingly, if you change the inputs to tell the program that you want to examine heights between 8 and 20 meters, i.e. quickLook smm3 2018 271 -h1 8 -h2 20 you now see what you expect to see - peaks of periodograms at ~16 meters height. Why is the northwest quadrant so messy? I leave that as an exercise for the reader. Hint: start out by trying to examine this site on Google Earth.

gnssir

This is the main driver for the GNSS interferometric reflectometry code.
You need a set of instructions for gnssir which are made using make_json_input.
The inputs for make_json_input are:

  • station name
  • latitude (degrees)
  • longitude (degrees)
  • ellipsoidal height (meters).

The station location does not have to be cm-level for the reflections code. Within a few hundred meters is sufficient.
For example:

make_json_input p101 41.692 -111.236 2016.1

If you happen to have the Cartesian coordinates (in meters), you can set -xyz True and input those instead of lat, long, and height.

It will use defaults for other parameters if you do not provide them. Those defaults tell the code an azimuth and elevation angle mask (i.e. which directions you want to allow reflections from), and which frequencies you want to use, and various quality control (QC) metrics. Right now the default frequencies are GPS only, e.g. L1, L2C and L5. The json file of instructions will be put in $REFL_CODE/input/p101.json. You should look at it to get an idea of the kinds of inputs the code uses. The default azimuths can be changed, but this needs to be done by hand. Some parameters can be set via the command line, as in:

make_json_input p101 41.692 -111.236 2016.1 -e1 5 -e2 10

This changes elevation angles to 5-10 degrees.

As discussed in Roesler and Larson (2018), there are two QC measures used in this code. One is the peak value of the peak in the periodogram. In the example below the amplitude of the most significant peak is ~17, so if you define the required amplitude to be 15, this one would pass. Secondly it uses a very simple peak to noise calculation. In this case the average periodogram amplitude value is calculated for a RH region that you define, and that is the "noise". You then take the peak value (here ~17) and divide by the "noise" value.
For water I generally recommend a peak to noise ratio of 2.7, but for snow 3.2-3.5 or so. It can be tricky to set these QC values in general.

Things that are helpful to know for the make_json_input inputs:

Names for the GNSS frequencies

  • 1,2,5 are GPS L1, L2, L5
  • 20 is GPS L2C
  • 101,102 Glonass L1 and L2
  • 201, 205, 206, 207, 208: Galileo frequencies
  • 302, 306, 307 : Beidou frequencies
  • Some json settings can be set at the command line. run make_json_input -h to see these. Otherwise, edit the json file.
  • e1 and e2 are the min and max elevation angle, in degrees
  • minH and maxH are the min and max allowed reflector height, in meters
  • desiredP, desired reflector height precision, in meters
  • PkNoise is the periodogram peak divided by the periodogram noise ratio.
  • reqAmp is the required periodogram amplitude value, in volts/volts
  • polyV is the polynomial order used for removing the direct signal
  • freqs are selected frequencies for analysis
  • delTmax is the maximum length of allowed satellite arc, in minutes
  • azval are the azimuth regions for study, in pairs (i.e. 0 90 270 360 means you want to evaluate 0 to 90 and 270 to 360).
  • wantCompression, boolean, compress SNR files
  • screenstats, boolean, whether minimal periodogram results come to screen
  • refraction, boolean, whether simple refraction model is applied.
  • plt_screen: boolean, whether SNR data and periodogram are plotted to the screen
  • NReg [min and max required] : define the RH region where the "noise value" for the periodogram is computed. This is used to compute the peak to noise ratio used i n QC.
  • (this option has been removed) seekRinex: boolean, whether code looks for RINEX at an archive

Simple example for my favorite GPS site p041

  • make_json_input p041 39.949 -105.194 1728.856 (use defaults and write out a json instruction file)
  • rinex2snr p041 2020 150 (pick up and translate RINEX file for day of year 150 and year 2020 from unavco )
  • gnssir p041 2020 150 (calculate the reflector heights)
  • gnssir p041 2020 150 -fr 5 -plt True (override defaults, only look at L5 SNR data, and periodogram plots come to the screen)

Where are the files for this example?

  • json is stored in $REFL_CODE/input/p041.json
  • SNR files are stored in $REFL_CODE/2020/snr/p041
  • Reflector Height (RH) results are stored in $REFL_CODE/2020/results/p041

This is a snippet of what the result file would look like

  • Amp is the amplitude of the most significant peak in the periodogram (i.e. the amplitude for the RH you estimated).
  • DelT is how long a given rising or setting satellite arc was, in minutes.
  • emin0 and emax0 are the min and max observed elevation angles in the arc.
  • rise/set tells you wehther the satellite arc was rising or setting
  • Azim is the average azimuth angle of the satellite arc
  • sat and freq are as defined in this document

If you want a multi-GNSS solution, you need make a new json file and use multi-GNSS orbits. And the RINEX file you use must have multi-GNSS SNR observations in it. p041 currently has multi-GNSS data in the RINEX file, so you can use it as a test.

  • make_json_input p041 39.949 -105.194 1728.856 -allfreq True
  • rinex2snr p041 2020 151 -orb gnss
  • gnssir p041 2020 151 -fr 201 -plt True (look at the lovely Galileo L1 data)

What should the periodogram plots look like? Until we have Jupyter notebooks, I recommend you look at the paper I wrote with Carolyn Roesler or the question section of my web app.. Note that a failed arc is shown as gray in the periodogram plots. And once you know what you are doing (have picked the azimuth and elevation angle mask), you won't be looking at plots anymore.

Bugs/Features I know about

I have been using teqc to reduce the number of observables and to decimate. I have removed the former because it unfortunately- by default - removes Beidou observations in Rinex 2.11 files. If you request decimation and fortran is set to True, unfortunately this will still occur. I am working on removing my code's dependence on teqc.

If there is interest, I will ask UNAVCO to implement the Fortran translation code automatically (i.e. download and compile it for you as part of the pypi install). But doing this myself is well beyond my skillset.

No phase center offsets have been applied to these reflector heights. While these values are relatively small, we do plan to remove them in subsequent versions of the code.

The L2C and L5 satellite lists are not time coded as they should be. I currently use a list from 2020.

Helper Codes

daily averages is a helper code for cryosphere people interested in daily snow accumulation. It can be used for lake levels. It is not to be used for tides!

download_rinex can be useful if you want to download RINEX v2 or 3 files (using the version flag) without using the reflection-specific codes. Sample calls:

  • download_rinex p041 2020 6 1 downloads the data from June 1, 2020

  • download_rinex p041 2020 150 0 downloads the data from day of year 150 in 2020

  • download_rinex p041 2020 150 0 -archive sopac downloads the data from sopac archive on day of year 150 in 2020

download_orbits downloads orbit files

ymd translates year,month,day to day of year

ydoy translates year,day of year to month and day

llh2xyz translates latitude, longitude, and ellipsoidal ht to X, Y, Z

xyz2llh translates Cartesian coordinates to latitude, longitude, height

download_tides downloads up to a month of NOAA tide gauge data given station number (7 characters), and begin/end dates, e.g. 20150601 would be June 1, 2015. The NOAA API works perfectly well for this, but this utility writes out a file with only numbers (which I always prefer) instead of csv. And I did not need to learn how to use pandas.

Publications

There are A LOT of publications about GPS and GNSS interferometric reflectometry. If you want something with a how-to flavor, try this paper, which is open option

Also look to the publications page on my personal website

How can I import the libraries in this package?

I will be adding more documentation and examples here.

If you wanted to run the gnssir code without the command line interface, here is an example for station p041 where the json instructions exist and the SNR file has already been created.

# my internal libraries you need
import gnssrefl.gps as g
import gnssrefl.gnssir as guts


station = 'p041' 
extension = ''  

# instructions for the Lomb Scargle Periodogram
lsp = guts.read_json_file(station, extension)

# set the year, doy, and type of snr file
year = 2020; doy = 150; snr_type =  99 
guts.gnssir_guts(station,year,doy, snr_type, extension, lsp)

Acknowledgements

People that helped me with this code include Radon Rosborough, Joakim Strandberg, and Johannes Boehm. I also thank Peter Shearer and Lisa Tauxe for some very nice Python lecture notes.

This documentation was updated on November 19, 2020.

Kristine M. Larson

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gnssrefl-0.0.47.tar.gz (8.7 MB view hashes)

Uploaded Source

Built Distribution

gnssrefl-0.0.47-py3-none-any.whl (8.9 MB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page