Image restoration of the asymmetric point spread function of a high-resolution remote sensing satellite with time-delayed integration

The calibration and validation team of the Korea Aerospace Research Institute has calibrated and validated the image data of the KOMPSAT-2 since the launch of KOMPSAT-2 on July 28, 2006. The asymmetric phenomenon of the point spread function of the KOMPSAT-2 image data is evident in both the along and the across direction, most likely because KOMPSAT-2 has a 1 m ground sample distance high-resolution camera with time-delayed integration. Furthermore, because KOMPSAT-2 is in space, the KOMPSAT-2 image data has been corrected with good results by means of modulation transfer function compensation.     

Variational Mode Decomposition for Rotating Machinery Condition Monitoring Using Vibration Signals

The failure of rotating machinery applications has major time and cost effects on the industry.Condition monitoring helps to ensure safe operation and also avoids losses.The signal processing method is essential for ensuring both the efficiency and accuracy of the monitoring process.Variational mode decomposition(VMD)is a signal processing method which decomposes a non-stationary signal into sets of variational mode functions(VMFs)adaptively and non-recursively.The VMD method offers improved performance for the condition monitoring of rotating machinery applications.However,determining an accurate number of modes for the VMD method is still considered an open research problem.Therefore,a selection method for determining the number of modes for VMD is proposed by taking advantage of the similarities in concept between the original signal and VMF.Simulated signal and online gearbox vibration signals have been used to validate the performance of the proposed method.The statistical parameters of the signals are extracted from the original signals,VMFs and intrinsic mode functions(IMFs)and have been fed into machine learning algorithms to validate the performance of the VMD method.The results show that the features extracted from VMD are both superior and accurate for the monitoring of rotating machinery.Hence the proposed method offers a new approach for the condition monitoring of rotating machinery applications.     

OSIRIS-REx: Sample Return from Asteroid (101955) Bennu

In May of 2011, NASA selected the Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) asteroid sample return mission as the third mission in the New Frontiers program. The other two New Frontiers missions are New Horizons, which explored Pluto during a flyby in July 2015 and is on its way for a flyby of Kuiper Belt object 2014 MU69 on January 1, 2019, and Juno, an orbiting mission that is studying the origin, evolution, and internal structure of Jupiter. The spacecraft departed for near-Earth asteroid (101955) Bennu aboard an United Launch Alliance Atlas V 411 evolved expendable launch vehicle at 7:05 p.m. EDT on September 8, 2016, on a seven-year journey to return samples from Bennu. The spacecraft is on an outbound-cruise trajectory that will result in a rendezvous with Bennu in November 2018. The science instruments on the spacecraft will survey Bennu to measure its physical, geological, and chemical properties, and the team will use these data to select a site on the surface to collect at least 60 g of asteroid regolith. The team will also analyze the remote-sensing data to perform a detailed study of the sample site for context, assess Bennu’s resource potential, refine estimates of its impact probability with Earth, and provide ground-truth data for the extensive astronomical data set collected on this asteroid. The spacecraft will leave Bennu in 2021 and return the sample to the Utah Test and Training Range (UTTR) on September 24, 2023.

     

Regolith X-Ray Imaging Spectrometer (REXIS) Aboard the OSIRIS-REx Asteroid Sample Return Mission

The Regolith X-ray Imaging Spectrometer (REXIS) is the student collaboration experiment proposed and built by an MIT-Harvard team, launched aboard NASA’s OSIRIS-REx asteroid sample return mission. REXIS complements the scientific investigations of other OSIRIS-REx instruments by determining the relative abundances of key elements present on the asteroid’s surface by measuring the X-ray fluorescence spectrum (stimulated by the natural solar X-ray flux) over the range of energies 0.5 to 7 keV. REXIS consists of two components: a main imaging spectrometer with a coded aperture mask and a separate solar X-ray monitor to account for the Sun’s variability. In addition to element abundance ratios (relative to Si) pinpointing the asteroid’s most likely meteorite association, REXIS also maps elemental abundance variability across the asteroid’s surface using the asteroid’s rotation as well as the spacecraft’s orbital motion. Image reconstruction at the highest resolution is facilitated by the coded aperture mask. Through this operation, REXIS will be the first application of X-ray coded aperture imaging to planetary surface mapping, making this student-built instrument a pathfinder toward future planetary exploration. To date, 60 students at the undergraduate and graduate levels have been involved with the REXIS project, with the hands-on experience translating to a dozen Master’s and Ph.D. theses and other student publications.     

Robust model predictive control for satellite formation keeping with eccentricity/inclination vector separation

This study presents model predictive formation control based on an eccentricity/inclination vector separation strategy. Alternative collision avoidance can be accomplished by using eccentricity/inclination vectors and adding a simple goal function term for optimization process. Real-time control is also achievable with model predictive controller based on convex formulation. Constraint-tightening approach is address as well improve robustness of the controller, and simulation results are presented to verify performance enhancement for the proposed approach.     

ExoMars Trace Gas Orbiter (TGO) Science Ground Segment (SGS)

The ExoMars Trace Gas Orbiter (TGO) Science Ground Segment (SGS), comprised of payload Instrument Team, ESA and Russian operational centres, is responsible for planning the science operations of the TGO mission and for the generation and archiving of the scientific data products to levels meeting the scientific aims and criteria specified by the ESA Project Scientist as advised by the Science Working Team (SWT). The ExoMars SGS builds extensively upon tools and experience acquired through earlier ESA planetary missions like Mars and Venus Express, and Rosetta, but also is breaking ground in various respects toward the science operations of future missions like BepiColombo or JUICE. A productive interaction with the Russian partners in the mission facilitates broad and effective collaboration. This paper describes the global organisation and operation of the SGS, with reference to its principal systems, interfaces and operational processes.     

Spin parameters of Low Earth Orbiting satellites Larets and Stella determined from Satellite Laser Ranging data

Satellite Laser Ranging (SLR) measurements contain information about the spin parameters of the fully passive, geodetic satellites. In this paper we spectrally analyze the SLR data of 5 geodetic satellites placed on the Low Earth Orbits: GFZ-1, WESTPAC, Larets, Starlette, Stella, and successfully retrieve the frequency signal from Larets and Stella only. The obtained signals indicate an exponential increase of the spin period of Larets: T = 0.860499·exp(0.0197066·D) [s], and Stella: T = 13.5582·exp(0.00431232·D) [s], where D is in days since launch. The initial spin periods calculated from the first month of the SLR observations are: Larets: T_initial = 0.8239 s, Stella: T_initial = 13.2048 s. Analysis of the apparent effects indicates the counter-clockwise spin direction of the satellites. The twice more heavy Stella lost its rotational energy more than four times slower than Larets. Fitting the spin model to the observed spin trends allows determination of the spin axis orientation evolution for Larets and Stella before their rotational period becomes equal to the orbital period.     

New results on spin determination of nanosatellite BLITS from High Repetition Rate SLR data

The nanosatellite BLITS (Ball Lens In The Space) demonstrates a successful design of the new spherical lens type satellite for Satellite Laser Ranging (SLR). The spin parameters of the satellite were calculated from more than 1000 days of SLR data collected from 6 High Repetition Rate (HRR) systems: Beijing, Changchun, Graz, Herstmonceux, Potsdam, Shanghai.     

On the detection of anomalous seismo-ionospheric behavior in the presence of space weather stimuli for large earthquakes

Anomalous behavior of ionospheric total electron content (TEC) prior to earthquake has been observed in many studies. Evidence of such seismo-ionospheric coupling effects suggests that it is plausible to rely on TEC signatures for early earthquake warning. However, the detection of pre-earthquake TEC anomalies (PETA) has not been adopted in practice due to two pertinent issues. Firstly, the effects of space weather activity can affect TEC levels and cause anomalous behavior in the TEC. Usually arbitrary thresholds are set for space weather indices to eliminate TEC anomaly due to space weather effects. Secondly, the choice regarding moving time-window length used to characterise background variation of TEC within the statistical envelope approach has an effect on detection of PETA. While the rule-of-thumb in selecting the moving window length is to have a time window capable of capturing background variability and short-term fluctuations, the length of the time window used in the literature varies with little justification. In this study, a critical examination is conducted on the statistical envelope approach and in particular, to eliminate the effect of space weather activity without the use of arbitrary space indices to detect PETA. A two-part PETA identification procedure is proposed, consisting of wavelet analyses isolating non-earthquake TEC contributions, followed by the statistical envelope method using a moving window length standardized based on observed periodicities and statistical implications is suggested. The approach is tested on a database of 30 large earthquakes (M?≥?7.0). The proposed procedure shows that PETA can be detected prior to earthquakes at higher confidence levels without the need to separately check for space weather activity. More importantly, the procedure was able to detect PETA for studies where it was previously reported that PETA could not be detected or detected convincingly.