Jean-Noël Pittet

Bio: Jean-Noël Pittet is an academic researcher from University of Bern. The author has contributed to research in topics: Space debris & Spacecraft. The author has an hindex of 5, co-authored 15 publications receiving 98 citations.

Comparison of ENVISAT’s attitude simulation and real optical and SLR observations in order to refine the satellite attitude model

Abstract: The Astronomic Institute of the University of Bern (AIUB) in cooperation with other three partners is involved in an ESA study dedicated to the attitude determination of large spacecraft and upper stages. Two major goals are defined. First is the long term prediction of tumbling rates (e.g. 10 years) for selected targets for the future Active Debris Removal (ADR) missions. Second goal is the attitude state determination in case of contingencies, when a short response time is required between the observations themselves and the attitude determination. One of the project consortium partners, hypersonic Technology Goettingen (HTG), is developing a highly modular software tool ιOTA to perform short- (days) to long-term (years) propagations of the orbit and the attitude motion of spacecraft in space. Furthermore, ιOTA's post-processing modules will generate synthetic measurements, e.g. light curves, SLR residuals and Inverse Synthetic Aperture Radar (ISAR) images that can be compared with the real measurements. In our work we will present the first attempt to compare real measurements with synthetic measurements in order to estimate the attitude state of tumbling satellite E NVISAT from observations performed by AIUB. We will shortly discuss the ESA project and ιOTA software tool. We will present AIUB’s ENVISAT attitude state determined from the SLR ranges acquired by the Zimmerwald SLR stati on. This state was used as the initial conditions within the ιOTA software. Consequently the attitude of satellite was predicted by using ιOTA and compared with the real SLR residuals, as well with the high frame-rate light curves acquired by the Zimmerwald 1-m telescope.

Debris Attitude Motion Measurements and Modelling by Combining Different Observation Techniques

Abstract: This work will discuss an ESA project “Debris Attitude Motion Measurements and Modeling” (ESA AO/1-7803/14/D/SR) dedicated to the attitude determination of large spacecraft and upper stages. Two major goals are defined for this project. First, the determination of the attitude motion vector in case of a contingency situation, when a short response time is required between the observations themselves and the attitude determination. The second goal is the long term prediction (e.g. 10 years) of the spin rate of selected targets for future potential Active Debris Removal (ADR) missions. The study should in particular fuse the results from passive optical, laser ranging and radar observations. We will discuss a highly modular software tool named ιOTA (In-Orbit Tumbling Analysis) which was developed during the presented activity. This tool performs short- (days) to long-term (years) propagations of the orbit and the attitude motion of spacecraft in Earth orbit and furthermore its post-processing modules will generate synthetic measurements, i.e. light curves, satellite laser ranging (SLR) residuals and synthet ic radar images. Last but not least we will present results from a collaborative campaign when four priority targets have been selected for collaborative measurements with radar, SLR and light curves in order to test and validate the ΙOTA tool.

Extensive light curve database of Astronomical Institute of the University of Bern

Abstract: Our paper will discuss the photometry observation techniques currently in use by the Astronomical Institute of the University of Bern (AIUB) and at the Zimmerwald observatory. We present the processing of light curves with the aim to determine apparent spin periods of observed objects and to reconstruct their folded phase functions. We will summarize spin rates for 397 objects extracted from 1991 light curves which were acquired with the ZIMLAT telescope during the last ten years. More than dozen of defunct spacecraft showed a periodic change of the apparent spin rates over time. These cases will be briefly discussed.

Orbital Debris Threat for Space Sustainability and Way Forward (Review Article)

Abstract: Over the past 60 years, satellite technology has demonstrated its usefulness successfully. However, this usefulness is at stake from a future point of view, due to the well-admitted orbital/space debris threat. This article thoroughly reviews all aspects of space debris issue including causes, amount and sizes of orbital debris, potential threats, counter-strategies with their latest status and related legal issues to highlight the criticality and urgency of the problem. This review elaborates the fact that despite all the worries and threats, the efforts to confront this challenge are considerably insufficient until today. This bitter reality demands for at-least curtailing the number of future launches to ensure the long-term sustainability of space, until the improvement in debris situation. However, contradictory to this necessity, large satellite constellations have been proposed that can drastically increase the existing orbital population in coming years. This approach will certainly not help in improving the space environment in the future; instead, it can worsen the space environment situation as recent studies shows. Also, space resources (i.e. orbital slots and frequencies) are limited to accommodate many more satellite projects from commercial and government organization in the future. So, there is a serious question of how the space industry can move forward to maintain a balance in controlling the future number of the satellite while accommodating many commercial or government space entities. This article also identifies two optimized approaches as a way forward for future satellite projects that can also enhance the effectiveness of space technology in the future.

Attitude Estimation and Geometry Reconstruction of Satellite Targets Based on ISAR Image Sequence Interpretation

Abstract: Analysis of the attitude and geometry of space targets with the inverse synthetic aperture radar (ISAR) technique is a significant and difficult task. Most of the existing methods hardly consider the radar observation geometry in the determination of target attitude. This paper proposes a novel approach to estimating the three-dimensional attitude and reconstructing typical component geometry of space targets from an ISAR image sequence. The approach bridges range-Doppler images and target attitude parameters with the accommodation of target trajectory information and the ISAR geometric projection model. By exploring the shape feature within the ISAR sequence, the target attitude and the rectangular component size are estimated through solving an optimization with prior shape constraints. Comparative experiments illustrate the advantages of the proposed method in both feature association and reconstruction feasibility. Moreover, considering practical circumstances, a further analysis is made of the robustness of the proposed algorithm after the attitude estimation experiment.

Space Debris Detection Using Feature Learning of Candidate Regions in Optical Image Sequences

Abstract: Space debris detection is important in space situation awareness and space asset protection. In this article, we propose a method to detect space debris using feature learning of candidate regions. The acquired optical image sequences are first processed to remove hot pixels and flicker noise, and the nonuniform background information is removed by the proposed one dimensional mean iteration method. Then, the feature learning of candidate regions (FLCR) method is proposed to extract the candidate regions and to detect space debris. The candidate regions of space debris are precisely extracted, and then classified by a trained deep learning network. The feature learning model is trained using a large number of simulated space debris with different signal to noise ratios (SNRs) and motion parameters, instead of using real space debris, which make it difficult to extract a sufficient number of real space debris with diverse parameters in optical image sequences. Finally, the candidate regions are precisely placed in the optical image sequences. The experiment is performed using the simulated data and acquired image sequences. The results show that the proposed method has good performance when estimating and removing background, and it can detect low SNR space debris with high detection probability.