KEYWORDS: Process control, Data processing, Computer architecture, Control systems, Network architectures, Amplifiers, Operating systems, Space operations
In this paper we describe the activities towards the design of a common framework for the Instrument Control and Data Processing Units for the three scientific payload instruments on board the joint ESA-JAXA SPICA mission, currently at the end of its phase A study. In this context, we started a program to assess modular architectures based on the use of a quad-core fault-tolerant LEON4 SPARC V8 processor on a SpaceWire network. We will describe the results of our initial tests using both Asymmetric Multi processing (AMP) and Symmetric Multi Processing (SMP) configurations. In addition, the possibility to adopt the RTEMS real time operating system, already space qualified on single core processors, will be evaluated both in terms of latency performances and of dynamical allocation of the resources. Finally, we will present the outline of the way forward for the next phases of the SPICA project.
KEYWORDS: Photometry, Picture Archiving and Communication System, Image quality, Image analysis, Bolometers, Data modeling, Neodymium, Distortion, Image processing, Data processing
We discuss Generalised Least Squares (GLS) map-making for the data of the Herschel satellite’s photometers, which is a difficult task, due to the many disturbances affecting the data, and requires appropriate pre- and post-processing. Taking an existing map-maker as a reference, we propose several advanced techniques, which can improve both the quality of the estimate and the efficiency of the software. As a main contribution we discuss two disturbances, which have not been studied yet and may be detrimental to the image quality. The first is a data shift, due to delays in the timing system or in the processing chain. The second is a random noise, termed pixel noise, due to the jitter and the approximation of the pointing information. For both these disturbances, we develop a mathematical model and propose a compensation method. As an additional contribution, we note that the performance can be improved by properly adapting the algorithm parameters to the data being processed and discuss an automatic setting method. We also provide a rich set of examples and experiments, illustrating the impact of the proposed techniques on the image quality and the execution speed.
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