Quickly get acquainted with Ginan.
Ginan is a precise point positioning software toolkit. It can calculate positions with centimetre-level accuracy using observations of global navigation satellite systems (GNSS) and correction data. It can also be used to create that correction data. More
Ginan is part of the Positioning Australia program. Positioning Australia is funded by the Australian Government and managed by Geoscience Australia. The Ginan team includes scientists and experts from Geoscience Australia, Australian and international academic institutions and FrontierSI. More
Ginan is provided by Geoscience Australia. The software is open source and free for anybody to download and use. Ginan is made available under the terms of the Apache License, version 2.0. More
The Ginan software is available from the Geoscience Australia GitHub site.
Geoscience Australia uses Ginan to produce precise positioning products and data correction streams. These are also free to use.
The name Ginan comes from the Wardaman people, traditionally living in the region south-west of Katherine in the Northern Territory, Australia. Ginan is a Wardaman word for a red dilly-bag filled with songs of knowledge and the fifth-brightest star in the Southern Cross. Just as the Southern Cross helped the First Australians to navigate this land, the positioning capability developed by Geoscience Australia will provide information on exactly where we are and where we are going. More
Ginan can be used for a wide range of applications that require centimetre level precise positioning. The Ginan team has identified sixteen use cases to date. They are:
For Academia
UC 1. As an aid to teaching GNSS technology for space based navigation, and geodesy and surveying courses.
UC 2. As a toolkit to help solve complex position, navigation and timing research challenges,
For Geoscience
UC 3. Work to maintain and improve Australia’s geodetic datums,
UC 4. Improve the performance of crustal movement and earthquake monitoring,
UC 5. To monitor the performance of networks of continuously operating reference stations (CORS).
UC 6. Detection of geohazards such as tsunamis, cyclones and space weather events through ionospheric disturbance monitoring.
For Industry
UC 7. Giving precise positioning to the Internet of Things (IoT) for new applications,
UC 8. On-selling correction products and streams with value-adding services,
UC 9. Calculating precise positions for general surveying, mapping and spatial related purposes,
UC 10. Making the user platform part of systems to bring precise positioning to mobile consumer devices e.g. phones, tablets. (Android, iOS),
UC 11. Running the user platform as embedded software for autonomous vehicles (land, sea, air, space),
UC 12. Precise orbit determination including LEO satellite fleets,
UC 13. Ground truthing objects to assist with space situational awareness.
For Government
UC 14. An alternative source of positioning data to check the performance of SouthPAN,
UC 15. As part of a system to monitor the performance of GNSS signals over the South Pacific,
UC 16. Use products such as the ZTD file to improve weather forecasting and climate change monitoring.
Other uses for Ginan will certainly appear in the future. Part of the reason for funding the development of Ginan was a desire by the Australian Government to stimulate the market in new products and services based on precise positioning. Ginan reduces the barriers for engaging in research, development, and experimentation in the use of precise positioning by being free and open source.
The science of calculating a position on Earth using observations of GNSS satellites is well known and has become a ubiquitous feature of our lives. Ginan uses the well-established State Space Representation (SSR) positioning model to enable users to achieve Precise Point Positioning (PPP). In the standard GNSS positioning process, small error sources limit the users calculated position accuracy at the meter level. The SSR methodology enables augmenting the users GNSS observations with corrections for those small errors, allowing Ginan to calculate PPP positions at the decimetre to millimetre level of accuracy, depending on the quality of PPP corrections used. More
At the heart of Ginan is a Kalman filter processing engine. The Kalman filter is an algorithm that takes observations received from GNSS satellites, and other auxiliary metadata, and produces estimates of unknown variables or states, such as the user’s position. The Ginan Kalman filter uses GNSS observations in their raw un-differenced form and can estimate all GNSS observation model states using either un-combined or the ionosphere free combination of the GNSS observations. More
There are three ways to get Ginan running:
You can download the Ginan binaries from the GitHub release website, either with or without the graphical user interface (GUI). These binaries work on Linux, MacOS and Windows. This can be found here: Ginan Releases
You can download the Ginan source code from the GitHub site, and the other required software packages, onto a Linux machine (including Windows Subsystem for Linux) and compile them to create the Ginan executable application. The instructions are in the Ginan README.
You can use Docker Desktop. Docker Desktop is a software application you can download onto a Linux, Mac or Windows computer. It creates a container that provides all the resources that the Ginan Docker image needs to run. Using Docker makes the process of getting started with Ginan simpler. You must download and install Docker Desktop, and then get the Ginan Docker image.
Ginan is a sophisticated software application with hundreds of parameters that control what it does. All these parameters are contained in configuration files using the yaml syntax (yaml - which might stand for "yet another markup language").
Ginan is released with example files to help users achieve particular outcomes. To understand more about Ginan's yaml files and parameters read the Ginan yaml guide.
Ginan relies on two basic types of input file. The first represents reference data. This includes things like lunar ephemerides, Earth rotation parameters and solid Earth tidal data. The second type contains data related to the GNSS satellites and receivers including the observations of the satellites. Observations can also be input to Ginan in continuous real-time streams. Organisations around the world supply all these different files and they are available from the internet. The yaml file is used to specify which files are needed to perform a particular processing activity. The yaml file documentation above provides more information.
If you have your own GNSS observations in a RINEX file Ginan can process them. The name of your file needs to be included in the yaml inputs section and the file(s) placed in the Ginan input data directory.
Ginan produces outputs in accordance with the parameter settings in the yaml file. Ginan has an outputs directory and outputs specific types of data in appropriate file formats such as SP3 for orbits and clocks. Ginan can also output data in trace files. Again, depending on the settings in the yaml file, trace files can contain intermediate results which may be of value. Ginan can also output data in real-time streams and send data to a Mongo database. Ginan has the Exploratory Data Analysis (EDA) tool which helps to visualise data.
Yes, through the usual GitHub mechanisms.
Not at this time. Ginan is written in C++ so it is possible to compile a version for Android and iOS but at the current time the Ginan team does not have plans to do it.
Ginan is free open-source software, developed in Australia. It can process GNSS observations in real-time from all the constellations. It has an ionosphere-free processing mode but can also process observations without combining or differencing them. It can resolve carrier wave ambiguities to integers and has an integrated and coupled precise orbit determination capability. Ginan has a support site.
You can send an e-mail to clientservices@ga.gov.au marked for the attention of the Ginan team, or raise an issue through GitHub.
The team welcome feedback on the Ginan toolkit including suggestions for improvements and new features.