What is Orbit Determination and why is it needed?
In its earliest form, orbit determination is generally said to date back to 1800’s with various early efforts made to observe, chart and understand the night sky.
Today, orbit determination serves as a foundational cornerstone to almost all modern telecommunications systems. It allows us to accurately discern not only the current, but the future position of satellites in orbit, a vital component to being able to transmit and receive data from these satellites, avoid collisions up in space and plan future space exploration missions.
The two questions at the core of Orbit Determination, both often easier said than answered.
How does Orbit Determination work and what makes it challenging?
Orbit determination works on the basis of gathering “observations” of satellites in orbit, and using these observations to deduce the satellites current state (position, velocity, etc). Using this information and applying an estimation theory, such as an Extended Kalman Filter (EKF), predictions about the future state of the satellite can be made. The predictions will vary in accuracy depending on factors such as the accuracy of the satellite’s current state guess, the confidence in the obtained measurements, and the prediction methodology applied. This so-called “covariance” or confidence in the satellites state forms an important factor in predicting potential collisions between satellites and ultimately ensuring the longevity of satellites in orbit.
Another key factor to the accuracy of an orbit determination solution lies in the frequency of available tracking observations. The more often measurements are available, the less time a satellite’s state has to grow in uncertainty due the various unknowns associated with its motion that begin to accumulate over time.
Tracking data from various known observations can be used to predict the satellite’s current state, alongside some uncertainty in that prediction, visualised here by the blue oval.
Visualisation of the Radial (Yellow), In-track (Teal) and Cross-track (Pink) components of Satellites state estimate.
The observations themselves can range from simple ground-based azimuth, elevation and range readings through to more complex space-based measurements from one satellite with a known orbit to another. Certain measurements will also inherently have larger uncertainties in particular dimensions than other. For example, a radar reading will generally provide better accuracy in the range direction than an optical observation. By comparison the optical observations may outperform a radar reading in the in-track or cross-track directions. For this reason, data fusion and the availability of various measurement types is often critical to obtaining an accurate orbit determination solution.
LEO Satellite with visualised covariance from two tracking sources (pink and green) as well as the combined, reduced covariance when both data sources are used for orbit determination.
Beyond the aforementioned uncertainties lie the behaviour of the satellite itself, particularly so if the user needs to perform orbit determination on an “uncooperative” satellite that is not their own. In such cases, the user requires a means with which they can accurately detect, model and account for manoeuvres that the satellite might perform. Often times these manoeuvres will occur between measurement access periods, making it incredibly difficult to keep track of uncooperative satellites without a robust method of orbit determination designed to tackle such problems.
Overall, it is imperative that all spacecraft and ground stations operators, as well the connected stakeholder’s dependent on satellite data transfers, possess a means for reliable and repeatable orbit determination which remains fast, highly accurate and scalable to all manner of challenges. For these reasons, orbit determination without the right tools is an incredibly difficult undertaking, which brings us to the industry standard tool for these challenges, Ansys Orbit Determination Tool Kit (ODTK).
An Introduction to Orbit Determination Tool Kit
The video above provides an overview of Ansys ODTK, its use cases and the general workflow with which it can ingest various data sources, perform highly accurate and rapid orbit determination, and crucially, facilitate the analysis and visualisation of those results.
It covers a very basic use case with a single LEO satellite and limited ground network of tracking stations, however ODTK remains capable of significantly more complex and involved cases.
Visualisation of a ground facility tracking a LEO satellite as it descends towards the horizon.
What if we don’t have real-world tracking data?
In a lot of instances, orbit determination work needs to be simulated to accurately plan a future space mission, ground station network, new antenna, etc. In these instances, real world tracking data is not yet available for analysis in ODTK. However, ODTK facilitates the design and testing of such systems via the inbuilt data simulator. This tool is capable of generating accurate tracking data for any manner of links, ground based or space-based measurements, and any supported measurement type. This simulated data can include system biases, white noise and any other factors affecting information accuracy. Ultimately, this capability allows for the accurate
Example of some simulated doppler measurements from a ground facility (REEF-A) to a LEO Satellite (Satellite1). In this instance, measurements are simulated every 60 seconds whenever line of sight is available between the ground facility and satellite.
ODTK Capabilities
Beyond the basic use case covered in the above video, ODTK is able to support any manner of orbit determination problems. This includes deep space tracking, cislunar missions and even surface vehicles on Earth or another central body. Crucially ODTK also provides a well-documented API for the automation and customisation of the tool for more involved or repeated tasks. This lends itself to an incredibly efficient orbit determination workflow, regardless of the data source, problem description or complexity. For more information on the capabilities of ODTK for a particular use case, please feel free to reach out to us at LEAP Australia and we’d be happy to organise a call/demo to showcase the tool for your specific needs.