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The Australian Government, through Positioning Australia (part of Geoscience Australia), is funding the design, development and operational service of a Global Navigation Satellite System (GNSS) position correction system - the Ginan service and toolkit. The application of the Ginan correction service by a GNSS device has the potential to increase positioning accuracy from meters to centimetres across Australia. The suite of software systems in this repository (the Ginan toolkit) will be used to create the service. It is available now under an open source licence. Ginan will give individuals and organisations no-cost access to the Ginan software and service as a public good.

Home Page: https://geoscienceaustralia.github.io/ginan/

License: Other

Shell 0.51% Dockerfile 0.01% Python 8.78% CMake 0.56% C++ 29.79% C 0.91% Makefile 0.01% Fortran 59.43%

ginan's Introduction

gn_logo

Ginan: software toolkit and service

Ginan v1.1-alpha release

Overview

Ginan is a processing package being developed to processes GNSS observations for geodetic applications.

We currently support the processing of:

  • the United States' Global Positioning System (GPS);
  • the Russian GLONASS system (GLONASS);
  • the European Union's Galileo system (Galileo);
  • the Chinese Navigation Satellite System (BeiDou);
  • the Japanese QZSS develop system (QZSS).

We are actively developing Ginan to have the following capabilities and features:

  • Precise Orbit & Clock determination of GNSS satellites (GNSS POD);
  • Precise Point Positioning (PPP) of GNSS stations in network and individual mode;
  • Real-Time corrections for PPP users;
  • Analyse full, single and multi-frequency, multi-GNSS data;
  • Delivering atmospheric products such as ionosphere and troposphere models;
  • Servicing a wide range of users and receiver types;
  • Delivering outputs usable and accessible by non-experts;
  • Providing both a real-time and off-line processing capability;
  • Delivering both position and integrity information;
  • Routinely produce IGS final, rapid, ultra-rapid and real-time (RT) products;
  • Model Ocean Tide Loading (OTL) displacements.

The software consists of two main components: Network Parameter Estimation Algorithm (PEA) and Precise Orbit Determination (POD).


Supported Platforms

Ginan is supported on the following platforms

  • Linux
  • MacOS

Download

You can download Ginan source from github using git clone:

$ git clone https://github.com/GeoscienceAustralia/ginan.git

Then download all of the example data using the python script provided:

$ python3 scripts/download_examples.py 

Directory Structure

ginan/
├── README.md			! General README information
├── LICENSE.md		    ! Software License information
├── aws/		        ! Amazon Web Services config
├── bin/		        ! Binary executables directory*
├── CMakeLists.txt		! Cmake build file
├── docs/			    ! Documentation directory
├── examples/           ! Ginan examples directory
│   ├── data/           ! example dataset (rinex files)**
│   ├── products/       ! example products and aux files**
│   ├── solutions/      ! example solutions for QC**
│   --------------PEA examples--------------
│   ├── ex11            ! PEA example 1
│   ├── ex12            ! PEA example 2
│   ├── ex13            ! PEA example 3
│   ├── ex14            ! PEA example 4
│   ├── ex15            ! PEA example 5
│   ├── ex17            ! PEA example 7
│   ├── ex18            ! PEA example 8
│   --------------POD examples--------------
│   ├── ex21            ! POD example 1
│   ├── ex22            ! POD example 2
│   ├── ex23            ! POD example 3
│   ├── ex24            ! POD example 4
│   ├── ex25            ! POD example 5
│   └── ex26            ! POD example 6
│
├── lib/		        ! Compiled objectlibrary directory*
├── scripts/		    ! Auxillary Python and Shell scripts and libraries
└── src/		        ! Source code directory
    ├── cpp/            ! PEA source code
    ├── fortran/        ! POD source code
    ├── cmake/   
    ├── doc_templates/
    ├── build/			! Cmake build directory*
    └── CMakeLists.txt

*created during installation process

**created by download_examples.py script


Dependencies

If you wish to use Ubuntu Linux, you can quickly create your environment by downloading the docker image:

$ docker pull gnssanalysis/ginan:v1.0-alpha

Otherwise Ginan has several software dependencies:

  • C/C++ and Fortran compiler. We use and recommend gcc-g++ and gfortran
  • BLAS and LAPACK linear algebra libraries. We use and recommend OpenBlas as this contains both libraries required
  • CMAKE > 3.0
  • YAML > 0.6
  • Boost > 1.70 (tested on 1.73)
  • Eigen3
  • netCDF4
  • Python3 (tested on Python 3.7)

Installing dependencies with Ubuntu

Update the base operating system:

$ sudo apt update
$ sudo apt upgrade

Install base utilities gcc, gfortran, git, openssl, openblas etc:

$ sudo apt install -y git gobjc gobjc++ gfortran libopenblas-dev openssl curl net-tools openssh-server cmake make libssl1.0-dev

Building additional dependencies

Depending on the user's installation choice: install PEA-only, POD-only or all software packages, a set of additional dependencies that need to be built may change. Below, we explain building all the additional dependencies:

First, create a temporary directory structure to make the dependencies in, it can be removed after the installation process is done:

$ sudo mkdir -p /data/tmp
$ cd /data/tmp

Note that /data/tmp is only used here as example and can be any directory

YAML

We are using the YAML library to parse the configuration files used to run many of the programs found in this library. Here is an example of how to install the yaml library from source:

$ cd /data/tmp
$ sudo git clone https://github.com/jbeder/yaml-cpp.git
$ cd yaml-cpp
$ sudo mkdir cmake-build
$ cd cmake-build
$ sudo cmake .. -DCMAKE\_INSTALL\_PREFIX=/usr/local/ -DYAML\_CPP\_BUILD\_TESTS=OFF
$ sudo make install yaml-cpp
$ cd ../..
$ sudo rm -fr yaml-cpp

Boost (PEA)

PEA relies on a number of the utilities provided by boost, such as their time and logging libraries.

$ cd /data/tmp/
$ sudo wget -c https://boostorg.jfrog.io/artifactory/main/release/1.73.0/source/boost_1_73_0.tar.gz
$ sudo gunzip boost_1_73_0.tar.gz
$ sudo tar xvf boost_1_73_0.tar
$ cd boost_1_73_0/
$ sudo ./bootstrap.sh
$ sudo ./b2 install
$ cd ..
$ sudo rm -fr boost_1_73_0/ boost_1_73_0.tar

Eigen3 (PEA)

Eigen3 is used for performing matrix calculations in PEA, and has a very nice API.

$ cd /data/tmp/
$ sudo git clone https://gitlab.com/libeigen/eigen.git
$ cd eigen
$ sudo mkdir cmake-build
$ cd cmake-build
$ sudo cmake ..
$ sudo make install
$ cd ../..
$ sudo rm -rf eigen

MongoDB (PEA, optional)

Needed for realtime preview of the processed results (developers-only)

$ wget https://github.com/mongodb/mongo-c-driver/releases/download/1.17.1/mongo-c-driver-1.17.1.tar.gz
$ tar -xvf mongo-c-driver-1.17.1.tar.gz

$ cd mongo-c-driver-1.17.1/
$ mkdir cmakebuild
$ cd cmakebuild/
$ cmake -DENABLE_AUTOMATIC_INIT_AND_CLEANUP=OFF ..
$ cmake --build .
$ sudo cmake --build . --target install

$ cd ../../
$ curl -OL https://github.com/mongodb/mongo-cxx-driver/releases/download/r3.6.0/mongo-cxx-driver-r3.6.0.tar.gz
$ tar -xzf mongo-cxx-driver-r3.6.0.tar.gz

$ cd mongo-cxx-driver-r3.6.0/

$ cd build/
$ cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=/usr/local ..
$ sudo cmake --build . --target EP_mnmlstc_core
$ cmake --build .
$ sudo cmake --build . --target install

$ wget -qO - https://www.mongodb.org/static/pgp/server-4.4.asc | sudo apt-key add -
$ echo "deb [ arch=amd64,arm64 ] https://repo.mongodb.org/apt/ubuntu focal/mongodb-org/4.4 multiverse" | sudo tee /etc/apt/sources.list.d/mongodb-org-4.4.list
$ echo "deb [ arch=amd64,arm64 ] https://repo.mongodb.org/apt/ubuntu bionic/mongodb-org/4.4 multiverse" | sudo tee /etc/apt/sources.list.d/mongodb-org-4.4.list

$ sudo apt update
$ sudo apt install mongodb-org 

$ sudo systemctl start mongod
$ sudo systemctl status mongod
$ mongod

netcdf4 (OTL package)

$ sudo apt -y install libnetcdf-dev libnetcdf-c++4-dev

Build

Prepare a directory to build in, its better practise to keep this seperated from the source code.

$ cd src
$ mkdir -p build
$ cd build

Run cmake to find the build dependencies and create the make file. If you wish to enable the optional MONGO DB utilities you will need to add the -DENABLE_MONGODB=TRUE flag. If you wish to compile an optimised version, typically this version will run 3 times faster but you may run into compile problems depending on your system, add the -DOPTIMISATION=TRUE flag:

$ cmake [-DENABLE_MONGODB=TRUE] [-DENABLE_OPTIMISATION=TRUE] ..

To build every package simply run make or make -j 2, where 2 is a number of parallel threads you want to use for the compilation:

$ make [-j 2]

To build specific package (e.g. PEA or POD), run as below:

$ make pea -j 2
$ make pod -j 2

This should create executables in the bin directory of Ginan.

Check to see if you can execute the PEA:

$ ../../bin/pea --help

and you should see something similar to:

PEA starting... (pea_pod_examples vbf8c9cc from Tue Jul 6 06:09:50 2021)
Options:
--help                      Help
--quiet                     Less output
--verbose                   More output
--very-verbose              Much more output
--config arg                Configuration file
--trace_level arg           Trace level
--antenna arg               ANTEX file
--navigation arg            Navigation file
--sinex arg                 SINEX file
--sp3files arg              Orbit (SP3) file
--clkfiles arg              Clock (CLK) file
--dcbfiles arg              Code Bias (DCB) file
--bsxfiles arg              Bias Sinex (BSX) file
--ionfiles arg              Ionosphere (IONEX) file
--podfiles arg              Orbits (POD) file
--blqfiles arg              BLQ (Ocean loading) file
--erpfiles arg              ERP file
--elevation_mask arg        Elevation Mask
--max_epochs arg            Maximum Epochs
--epoch_interval arg        Epoch Interval
--rnx arg                   RINEX station file
--root_input_dir arg        Directory containg the input data
--root_output_directory arg Output directory
--start_epoch arg           Start date/time
--end_epoch arg             Stop date/time
--run_rts_only arg          RTS filename (without _xxxxx suffix)
--dump-config-only          Dump the configuration and exit
--input_persistance         Begin with previously stored filter and 
                            navigation states
--output_persistance        Store filter and navigation states for restarting
PEA finished

Similarly, check the POD:

$ ../../bin/pod --help

This returns:

Earth Radiation Model (ERM):   1

Default master POD config file = POD.in
To run from default config file: ../../bin/pod or ../../bin/pod -c POD.in

POD.in config file options by defaut can be overridden on the command line

Command line: ../../bin/pod -m -s -o -a -p -r -t -n -i -u -q -k -w -y -h 

Where: 
    -m --podmode = POD Mode:
                                1 - Orbit Determination (pseudo-observations; orbit fitting)
                                2 - Orbit Determination and Prediction
                                3 - Orbit Integration (Equation of Motion only)
                                4 - Orbit Integration and Partials (Equation of Motion and Variational Equations)
    -s --pobs    = Pseudo observations orbit .sp3 file name
    -o --cobs    = Comparison orbit .sp3 file name
    -a --arclen  = Orbit Estimation Arc length (hours)
    -p --predlen = Orbit Prediction Arc length (hours)
    -r --eopf    = Earth Orientation Paramaeter (EOP) values file
    -t --eopsol  = Earth Orientation Paramaeter file type: (1,2,3)
                                1 - IERS C04 EOP
                                2 - IERS RS/PC Daily EOP
                                3 - IGS RP + IERS RS/PC Daily (dX,dY)
    -n --nutpre  = IAU Precession / Nutation model
                                2000 - IAU2000A
                                2006 - IAU2006/2000A
    -i --estiter = Orbit Estimatimation Iterations (1 or greater)
    -u --sp3vel  = Output .sp3 file with velocities
                                0 - Do not write Velocity vector to sp3 orbit
                                1 - Write Velocity vector to sp3 orbit
    -q --icmode  = Initial condition from parameter estimation procedure
    -k --srpmodel= 1: ECOM1, 2:ECOM2, 12:ECOM12, 3:SBOX
    -w --empmodel= 1: activated, 0: no estimation
    -d --verbosity = output verbosity level [Default: 0]
    -y --yaml = yaml config file
    -h --help.   = Print program help

Examples:

        ../../bin/pod -m 1 -q 1 -k 1 -w 0 -s igs16403.sp3 -o igs16403.sp3 -y ex1.yaml
        ../../bin/pod -m 2 -q 1 -k 1 -w 0 -s igs16403.sp3 -p 12 -y ex2.yaml

For orbit updates using Parameter Estimation Algorithm (PEA):
        ../../bin/pod -m 4 -q 2 -k 1 -w 0 -s igs16403.sp3 -o igs16403.sp3 -y ex3.yaml

Documentation

Ginan documentation consists of two parts: a doxygen-generated documentation that shows the actual code infrastructure and a detailed manual, written in latex, that provides an overview of the software, a thoretical background, a detailed "how to" guide etc. Below, we explain on how to generate each bit of documentation:

Doxygen

The Doxygen documentation for Ginan requires doxygen and graphviz. If not already installed, type as follows:

$ sudo apt -y install doxygen graphviz

On success, proceed to the build directory and call make with doc_doxygen target:

$ cd src/build
$ make doc_doxygen

The docs can then be found at docs/html/index.html. Note that documentation is generated automatically if make is called without arguments and doxygen and graphviz dependencies are satisfied.

Latex

A detailed Ginan manual is located in docs/manual and is in latex format. To compile Latex to pdf you will need a compiler, such as texlive:

$ sudo apt install texlive-latex-base texlive-latex-extra

Now, go to docs/manual and generate the pdf:

$ cd docs/manual
$ pdflatex main.tex
$ makeglossaries main
$ pdflatex main.tex

main.pdf file should now appear in the directory.


Ready!

Congratulations! You are now ready to trial the examples of PEA and POD from the examples directory. See Ginan's manual for detailed explanation of each example. Note that examples have relative paths to files in them and rely on the presence of products, data and solutions directories inside the examples directory. Make sure you've run download_examples.py from the Download step of this instruction.

The paths are relative to the examples directory and hence all the examples must be run from the examples directory.

cd ../../examples

To run the first example of the PEA:

../bin/pea --config ex11_pea_pp_user_gps.yaml

This should create ex11 directory with ex11-ALIC201919900.TRACE and ex1120624.snx output files. You can remove the need for path specification to the executable by adding Ginan's bin directory to ~/.bachrc file:

PATH="path_to_ginan_bin:$PATH"

And an example of POD:

../bin/pod -y ex21_pod_fit_gps.yaml

At the completion of the test run, ex21 directory should be create. The ex21_.sh script will return any differences to the standard test resuts.


Python Installation for Plotting, Processing, etc.

Lastly, to run many of the included scripts for fast parsing of .trace/.snx files, plotting of results, automatic running of the PEA based on input date/times and stations, etc. then a number of python dependencies are needed.

The file scripts/conda_gn37.yaml has a list of the necessary python dependencies. The best way to take advantage of this is to install the Miniconda virtual environment manager. This will allow you to pass the .yaml file into the conda command and automatically set up a new python environment.

Install Miniconda

To install Miniconda, download and execute the Miniconda shell file:

$ wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
$ bash Miniconda3-latest-Linux-x86_64.sh

And follow the on-screen instructions (choosing all defaults is fine).

Create virtual environment

After installation you can create the gn37 python environment using a prepared receipy. First open a new terminal session and enter:

$ conda env create -f <dir_to_ginan>/scripts/conda_gn37.yaml

You have now created the virtual python environment gn37 with all necessary dependencies. Anytime you wish you run python scripts, ensure you are in the virtual environment by activating:

$ conda activate gn37

And then run your desired script from the scripts directory.

ginan's People

Contributors

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