• Current congress
• Public Website
• My papers
• root
• browse
• IAC-13
• B4
• 3
• paper
• # Fully Automated Mission Planning Tool for DEIMOS-2 Agile Satellite

Paper number

IAC-13,B4,3,2,x19131

Author

Mr. Matthias Renard, Deimos Space S.L., Spain

Coauthor

Dr. Stefania Tonetti, Deimos Space S.L., Spain

Coauthor

Ms. Blanca Altés-Arlandis, Deimos Space S.L., Spain

Coauthor

Ms. Stefania Cornara, Deimos Space S.L., Spain

Coauthor

Mr. Fabrizio Pirondini, Deimos Space S.L., Spain

Year

2013

Abstract
The DEIMOS-2 mission, slated for launch at the end of 2013, is aimed at operating an agile small satellite for high-resolution Earth Observation applications. The spacecraft can be steered to accurately point the payload up to 45 deg off-nadir. It will provide 75-cm pan-sharp and 4-m multi-spectral images with a 12-km swath at an altitude between 590 km and 640 km.

The platform agility makes it often necessary to choose one target amongst various, contemporaneously observable ones. When the workload grows, this combinatorial task becomes rapidly cumbersome for human operators and automation emerges as a key enabler for the mission planning and exploitation process. This paper presents a {\bf tool producing feasible acquisition sequences from a set of user areas of interest}. By feasible, we mean they do not overlap and they fulfil the platform constraints: attitude manoeuvring agility and stability requirements, on-board memory and downlink, power production and battery capacity.

In order to deal with various types of image requests, such as pin-point targets and extended mapping areas, an analysis of the best way to sample the ground surface has been performed, leading to a country-based composite grid aligned on the satellite ground track. It optimizes the mission observation return while allowing efficient management of the image catalogue.

All user-requested areas of interest are translated into sets of grid scenes, which are gathered into along-track stripes called targets. They are assigned a priority level reflecting their urgency/profitability and then fed into a greedy scheduler building a feasible acquisition sequence step-by-step. It schedules the observation of each target so as to fulfil the priority criterion and the system constraints. Attitude, power and dataflow models balance accuracy and speed so that small margins are needed to guarantee feasibility and the scheduling process is fast enough.

Besides the significant workflow enhancement obtained by the full automation of mission planning, the tool is also able to optimize the mission return by repeating the scheduling exercise and selecting the best-performing timeline. A sequencer reorders the targets within their priority groups, thus letting the scheduler generate different feasible timelines. Their goodness is evaluated by a function reflecting the mission commercial objectives and driving this optimization iteration.

Several approaches including evolutionary algorithms are currently under investigation and have provided promising results for realistic planning timeframes. Further constraints models including cloud forecast and acquisition outages are also being embedded to lead to a fully operational facility.
Abstract document

IAC-13,B4,3,2,x19131.brief.pdf

Manuscript document

IAC-13,B4,3,2,x19131.pdf (🔒 authorized access only).