Rocket science: Catch space rockets using unmanned vehicles
Background
Although Norway, lead by Andøya Space, is small space nation, we have space history going back to 1962 when the first Norwegian rocket was launched into space. With the new space port that is under construction at Andøya, the demand for space competence is increasing.
Recent developments by RocketLabs and SpaceX, seen in the videos below, has shown that recovering space rockets is not only possible, but tractable from both an economic and an environmental aspect.
| SpaceX | RocketLabs |
|---|---|
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To make this feasible for smaller/cheaper rockets it needs to be scaled down, and ideally utilize unmanned vehicles. Is this possible?
Scope
Initial studies shows that recovery of high-powered student rockets using fast unmanned surface vehicle(s) is possible, and has potential to reduce cost and environmental impacts of space activities. We are now looking at ways to further improve the method. A crucial component in the recovery is the prediction of the point where the rocket will hit the surface; the impact point. Currently the impact point is predicted by simulating the rocket position forward in time using simple ballistic equations. Some notable simplifications is the constant-mass assumption (the rocket consumes a lot of fuel), ignoring thrust, and not considering the attitude of the rocket when estimating the drag force.
Proposed tasks
The following indicates some possible focus areas of the project/master thesis. The list is by no means conclusive. We will discuss this, and find the best way forward that matches the student and the project.
- Familiarize with the space industry, focusing on rocket launch and recovery
- Review existing methods for impact point prediction, including the Kalman filter and optimization-based methods
- Improve rocket position and attitude estimation, by e.g. sensor fusion of GNSS, IMU, radar and slant range measurements.
- Investigate performance gains from increasing the complexity of the prediction model (variable mass, drag as a function of attitude, thurs model,…). How is robustness affected?
- Conclude the work in a written repoert
Prerequisites
This is a list of recommended prerequisites, more to signal what it will involve than to be used as a filter on candidates.
- Kalman filtering, from e.g. TTK4115 Linear Systems Theory TTK4250 Sensor Fusion, TTK4190 Guidance and Control of Vehicles and/or optimization from e.g. TTK4135 Optimization and Control
- Interest in space technology. From e.g. NTNUs courses on space technology 1 and 2.
Contact
Contact supervisor Kristoffer Gryte.