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Thales Alenia Space is designing and developing space observation instruments since more than 40 years. This paper explains why active optics is needed for next generation of instruments for Earth observation. It describes what kind of solution is preferred and gives an overview of the development status on the associated technologies. Indeed, the future missions will have to deal with better performance, better optical quality while from manufacturing point of view, the total mass, the development schedule and the final cost have to be reduced. These constraints induce a new generation of solutions based on large entrance optics associated to high lightweight ratio which naturally provide solutions sensitive to gravity deformation. In these conditions, the enhancement of the final performance can only be guaranteed by using active optics in flight. A deformable mirror is therefore foreseen to be implemented in future large telescopes in order to correct manufacturing residues and ground/flight evolution, including gravity. Moreover, low mass and low cost require more compact designs which entail solutions more sensitive to misalignment. An active positioning mechanism is then also needed in order to correct the telescope alignment during operation conditions. Thales Alenia Space has been selected by CNES to develop and qualify active optics building blocks and then to test and demonstrate the improvement that new active technologies can bring in a full size instrument representative of the next generation of observation instruments. An overview of the current development status and the achieved performances is given for each building block (Primary Mirror, deformable mirror, 6-dof mechanism, wavefront sensor).

Detecting change points in time series data is a challenging problem, in particular when no prior information on the data distribution and the nature of the change is available. In a former work, we introduced an online non-parametric change-point detection framework built upon direct density ratio estimation over two consecutive time segments, rather than modeling densities separately. This algorithm based on the theory of reproducing kernels showed positive and reliable detection results for a variety of problems. To further improve the detection performance of this approach, we propose in this paper to modify the original cost function in order to achieve unbiasedness of the density ratio estimation under the null hypothesis. Theoretical analysis and numerical simulations confirm the improved behavior of this method, as well as its efficiency compared to a state of the art one. Application to sentiment change detection in Twitter data streams is also presented.

Change-points can be defined as the time instants at which the underlying properties of a time series change. Detecting such points can be very challenging, especially when no prior information is available on the data distribution and the nature of the change. This paper introduces an onlin e nonparametric kernel-based change-point detection method built upon the direct density ratio estimation of two consecutive segments of the time series. Algorithms operating in re-producing kernel Hilbert spaces have demonstrated superiority over their linear counterparts, mainly because of their ability to deal with nonlinear problems with few prior information. However their major drawback lies in the linear growth of the models order with the number of input data, which dramatically increases computational cost and memory requirement. In addition to selecting a reproducing kernel and estimating the model parameters, designing a kernel-based model requires to determine a dictionary in order to get a finite-order model. This dictionary has a significant impact on performance, and requires careful consideration. As each new data point arrives, our algorithm updates the dictionary used to approximate the density ratio based on the coherence criterion. Then it updates the parameters of the model using the kernel least mean squares algorithm. Conditions for mean stability and asymptotic unbiasedness of our method are obtained under the null hypothesis for Gaussian input data. Mean-squared error is also studied. Finally, detection performances are evaluated by computer simulations.

The payloads for Earth Observation and Universe Science are currently based on very stiff opto-mechanical structures with very tight tolerances. The introduction of active optics in such an instrument would relax the constraints on the thermo-mechanical architecture and on the mirrors polishing. A reduction of the global mass/cost of the telescope is therefore expected. Active optics is based on two key-components: the wave-front sensor and the wave-front corrector.

The next generation of large lightweight space telescopes will require the use of active optics systems to enhance the performance and increase the spatial resolution. Since almost 10 years now, LAM, CNES, THALES and ONERA conjugate their experience and efforts for the development of space active optics through the validation of key technological building blocks: correcting devices, metrology components and control strategies. This article presents the work done so far on active correcting mirrors and wave front sensing, as well as all the facilities implemented. The last part of this paper focuses on the merging of the MADRAS and RASCASSE test-set up. This unique combination will provide to the active optics community an automated, flexible and versatile facility able to feed and characterise space active optics components.

International audience; The deployment of an application onto a multicore architecture is often a long and difficult process. This is due to the fact that the characteristics of both the architecture and the application are taken into account late in the development process. It's therefore necessary to have tools pruning the solution space efficiently and accurately. In order to define such a tool, this work defines the basic metrics and step for a design space exploration ("DSE") flow. To this end our proposal have been tested and validated for a space application that requires both a high computing power and an architecture compatible with the space constraints. The results obtained are promising and have shown the viability of the approach.