Christoph Lenzen

TerraSAR-X Mission Planning System: Automated Command Generation for Spacecraft Operations

On June 15, 2007, TerraSAR-X was successfully launched from Baikonur, Kazakhstan. On board TerraSAR-X, a high-resolution X-band synthetic aperture radar (SAR) instrument is being operated as the primary payload. The user community requesting SAR products is composed of commercial and scientific partners as documented in a public-private-partnership agreement. The operations of the TerraSAR-X bus as well as payload operations are performed by the Mission Operations Segment (MOS). The Mission Planning System (MPS), which is a part of the MOS, has been designed to handle complex payload and standard bus operations in an automated manner. The purpose of this paper is to describe the concepts and the TerraSAR-X realization of the MPS.

The joint TerraSAR-X / TanDEM-X mission planning system

This paper recalls the essential system requirements and elements for the joint TerraSAR-X / TanDEM-X mission planning system. Its commissioning approach, tests and results are described in detail.

TerraSAR-X/TanDEM-X Mission Planning Handling Satellites in Close Formation

This paper presents mission planning aspects of the future TanDEM-X mission scheduled for launch in 2010. In 2007 the TerraSAR-X satellite was successfully launched. Its payload consists of an earth observing Synthetic Aperture Radar, which supplies high resolution radar images. The primary goal of the TerraSAR-X mission is to supply the commercial and scientific users with radar image data on request. The TanDEM-X satellite is a nearly identical copy of the TerraSAR-X satellite. The two satellites will be orbiting the Earth in a close formation with distances from 250m to 500m. The radar instruments on both satellites may be used synchronously in a bi-static mode: One or both satellites actively transmit radar pulses; the echo is received by both satellites. This configuration gives a stereoscopic view such that information comprising all three dimensions can be retrieved from the data. The TanDEM-X mission goal is to generate a digital elevation model covering the whole Earth’s surface. In addition, the radar instruments on both the TerraSAR-X and the TanDEM-X satellites will still be operated in the TerraSAR-X mono-static mode and therefore both satellites may support the TerraSARX mission goals. The combined TerraSAR-X / TanDEM-X mission planning system will handle the two satellites as well as two completely different missions with their different mission goals. As a consequence, the new combined TerraSAR-X / TanDEM-X mission planning system not only has to support two satellites with their mutual constraints, but also will handle two different missions at the same time: the long-term mapping approach of the TanDEM-X mission and the short-term on-demand approach of the TerraSAR-X mission. There are two critical issues regarding the operational safety of the formation flight: the close distance of the two satellites implies a significant collision risk in case of anomalies. Next, illuminating the other satellite with radar pulses can cause severe damage to the illuminated satellite.

Tailoring the TerraSAR-X Mission Planning System to PPP Needs

The TerraSAR-X earth-observing radar mission, scheduled for launch in October 2006, has been set up as a public private partnership (PPP) to serve both scientific and commercial needs. The TerraSAR-X ground segment has to deal with the scientific community on the one hand and a commercial exploiter on the other hand. The mission planning system has been designed to satisfy the scientific and commercial partners, having own structures and motivations and sometimes-diverging interests, in the frame of a common mission. Both partners are interested in a schedule that is stable with respect to the time. Also the commercial exploiter has the strong interest to provide his final customers with reliable information. For a stable schedule, order behaviour is crucial: the more orders are known in advance, the more steady the execution timeline will behave in time. On the science side, the science coordinator will guide the individual scientists and their orders in a review process. As a result, the typical science order will be set up and fed into the system well in advance of the envisaged execution time. On the other side, the nature of the commercial market will lead to orders that come in just-i n-time and have to be scheduled and produced as fast as possible. In addition, there will be short-time high-priority orders from both sides as well as the need to schedule data-takes in respond to emergency tasks. As a consequence, the task of establishing an optimising planning process is demanding: The high-priority orders, with execution times in the very near future, will conflict with the already established schedule. Even during the design and implementation phase, the mission planning system had to be adapted to the changing needs of the commercial market leading to new requirements. On such a basis, the optimisation criteria for the planning process are hard to quantify. As a solution, the TerraSAR-X planning system implements a priority concept, agreed by the science and commercial part. A quota concept wi ll make sure that both sides will get, on time average, a fair share of the satellite resources. Periodical strategic planning meetings, with members from the science and commercial side as well as from mission management, will be supported by experienced mission planning engineers with statistical information regarding the past mission as well as the order situation in the future. The paper will outline the experiences as by shortly before the launch. It will describe how initial concepts had to be modified and where add-ons emerging from the starting commercialisation affected the system design.

The Algorithm Assembly Set of Plato

Driven by the requirements of earth observing satellite missions, the mission planning team of the German Space Operations Center (GSOC) has improved its scheduling engine to allow automated timeline generation for multiple interacting satellites. Whereas the past work included extensions of the modeling language and improvements on the performance, current work focusses on the algorithm framework. In order to allow future missions’ scheduling software to reuse generic algorithms, special attention is given to the way one can add new sub-algorithms and combine them with existing ones. This ePoster demonstrates the algorithm framework of GSOC’s mission planning software Plato, using its interactive GUI Pinta. Based upon a typical multiple satellite planning problem, a priority based generic algorithm is presented, which solves this problem. We show how this algorithm can be split up into small subalgorithms, each of which can be used separately and all of which can be combined in arbitrary ways. We demonstrate how this flexibility can be used to create modifications on the overall algorithm or include mission specific sub-algorithms. Although all presented algorithms are based on simple heuristics, this mechanism supplies a straight forward way to incorporate more sophisticated optimization algorithms. The techniques demonstrated in this paper will be shown by means of the OnCall planning project. This project is used by GSOC in order to schedule the on-call shift times of its staff in order to implement 24/7 support for all important satellite sub-systems.

Mission Planning System for the TET-1 OnOrbitVerification Mission

The TET-1 satellite was launched on July 22nd, 2012, to test and demonstrate the space readiness of new hardware components. Eleven experiments are running in space since then. The mission planning system (MPS) that provides the TET-1 satellite with its tele-command timelines during the OnOrbitVerification (OOV) phase is presented: Based on a strategic one-year experiment plan provided in advance by an external industry partner, MPS collects all relevant information necessary to build a sequence of flight procedures, called timeline, for a time range of roughly a week, on a day-by-day basis. In contrast to the TerraSAR-X/TanDEM-X MPS or the Incremental Planning System, where several software components convert incoming orders into commandable files, a slim set of tools was decided to be used for the TET-1 mission, combined in PINTA (Program for INteractive Timeline Analysis). Necessary data was imported using the plug-in mechanism of PINTA that uses interfaces to several partners. Having all information available, scheduling itself was done by running the planning algorithms provided by Plato, GSOCs generic library for modeling and solving planning problems. An assembly of various planning algorithms, individually configurable and referencing one another, creates the necessary timeline entries of flight procedures. Due to the high flexibility of the planning system it was possible to support various changes in the pre-planned onboard timeline on short notice. Additionally, an outlook on further extensions of the current MPS is given, that enables even more flexibility in terms of data acquisition and are relevant for the upcoming FireBIRD mission, which includes the TET-1 spacecraft after the OOV operations phase.

Onboard Planning and Scheduling Autonomy withinthe Scope of the FireBird Mission

For most low orbiting earth observation satellite missions, the timeline is generated on- ground and during dedicated uplink sessions the corresponding tele-commands are sent to the spacecraft. Bene�ts of this approach are easy maintainability of the complex planning software and quick response times to customer input. However this approach has two major drawbacks: On the one hand the spacecraft behavior is not completely predictable in terms of constraining resources, which means that even detailed modeling requires margins for the on-board resources within the on-ground scheduling algorithms. On the other hand, the reaction time to onboard detected events includes at least the two upcoming ground station contacts, since data downlink and evaluation, (re-)planning and tele-command uplink have to be awaited before the spacecraft can perform new activities. This paper describes the �nal design and use cases of VAMOS, an experiment of DLR/GSOC, which will be part of the FireBird mission. VAMOS consists of a combined onboard / on-ground planning system, which resolves the above mentioned drawbacks by supplying limited onboard autonomy to the satellite, retaining the bene�ts of a ground based planning system as far as possible.

VAMOS – Verification of Autonomous Mission Planning On-board a Spacecraft

For typical ground based mission planning systems for low earth satellite missions one major drawback can be detected: The reaction time to on-board-detected events, which includes at least two ground station contacts. To correct this, the DLR/GSOC invented VAMOS, which is an autonomous concept of minimized on-board complexity which allows on-board reaction to telemetry measurements and event detection. This experiment will be part of the FireBIRD mission and verify the gain when mission planning autonomy is transferred to the spacecraft up to some extent. This paper presents the outcome of the design phase under the given constraints. In order to minimize risks and computational effort on-board, a solution has been chosen that demands relatively simple tasks of the on-board autonomy but nevertheless will lead to maximizing the mission output and on the other hand takes care of all potentially to be considered resource constraints.

The Incremental Planning System—GSOC's Next- Generation Mission Planning Framework

The paper at hand presents the new generic framework for automated planning and scheduling in future mission planning systems developed at GSOC (German Space Operations Center). It evolved from the experiences made in past and current projects and the evaluation of internal and external requirements for upcoming projects. In customary systems such as the one used within GSOC’s TerraSAR-X/TanDEM-X mission, succeeding planning runs to combine all collected input to a consistent, conflict-free command timeline take place at fix, dedicated points in time, e.g. twice a day. In contrast and as a main difference, with the new system each new input is processed immediately and so a consistent up-to-date timeline is maintained at all times. We show that this approach provides a set of important advantages and new possibilities for spacecraft commanding and user satisfaction. For example, uplink schedules can be flexibly modified due to short-term notifications, or up-to-date, extensive information about the planning state is always available, which means that conflicts can be seen before finally submitting a new request and, if applicable, can be resolved by selecting a suggested solution scenario. The presented system constitutes a generic tool suite which is scalable in performance critical areas, which is configurable to various mission scenarios and which defines a dedicated set of interfaces, specifying the functionality that remains to be implemented by each individual project. The declared goal is that all upcoming GSOC missions will benefit from using the Incremental Planning framework in terms of cost reduction, implementation duration and system robustness.

Scheduling Formations and Constellations

The timeline generation process for complex systems is usually executed at multiple levels of granularity. This allows splitting the overall scheduling problem into smaller subsystems of less complexity. However this implies a degradation of the solution , because each subsystem must be restricted such that any solution of the other subsystems must be feasible. An obvious example is envelope planning, such as time sharing: two partners realize a satellite project. In return, each of them receives time slots where he can use the satellites pa yload. The Pinta-Plato software can help reducing the number of levels of granularity and still keep the system clear and manageable to implement and to maintain. The key feature for integrating these multiple layers is the descriptive and powerful modeling language, which has been designed for flexible modelling, rather than to support specialized optimization algorithms. Nevertheless an elaborated calculation engine is part of the Plato library, which supplies all functionalities needed to implement a tailored heuristic algorithm for the specific model . An example will be presented which takes this even one step further: a multi -satellite scheduling project will be presented, including a model of available ground station antennas. Due to the fact that we have an integrated model, constraints may be defined in between all of the satellites and ground stations, which means that the complex interactions of constellations and formations may be included in our model. Although the resulting scheduling problem inc ludes some tricky dependencies, we will show how easily this problem may be solved with the generic features of our scheduling engine.