33 results found
Chen S, Amato D, 2022, Dynamical characterization of endogenous conjunctions within the Starlink constellation, 33rd AAS/AIAA Space Flight Mechanics Meeting
Enríquez Fuentes C, Amato D, 2022, Application of LSTMs to the light curve inversion problem, 33rd AAS/AIAA Space Flight Mechanics Meeting
Cho N, Shin H-S, Tsourdos A, et al., 2022, Incremental Correction in Dynamic Systems Modelled with Neural Networks for Constraint Satisfaction
This study presents incremental correction methods for refining neural network parameters or control functions entering into a continuous-time dynamic system to achieve improved solution accuracy in satisfying the interim point constraints placed on the performance output variables. The proposed approach is to linearise the dynamics around the baseline values of its arguments, and then to solve for the corrective input required to transfer the perturbed trajectory to precisely known or desired values at specific time points, i.e., the interim points. Depending on the type of decision variables to adjust, parameter correction and control function correction methods are developed. These incremental correction methods can be utilised as a means to compensate for the prediction errors of pre-trained neural networks in real-time applications where high accuracy of the prediction of dynamical systems at prescribed time points is imperative. In this regard, the online update approach can be useful for enhancing overall targeting accuracy of finite-horizon control subject to point constraints using a neural policy. Numerical example demonstrates the effectiveness of the proposed approach in an application to a powered descent problem at Mars.
Cho N, Amato D, 2022, Enforcing state constraints in dynamical systems modelled with neural networks, International Conference on Computational Science 2022
Deep neural networks (NNs) are usually trained with unconstrained optimisation algorithms. With a reasoning similar to the constrained Kalman filter, incorporating known information in the form of equality constraints at certain checkpoints can potentially improve prediction accuracy. For continuous-time dynamical systems, the state constraints should be enforced in an ordinary differential equation (ODE) model which embeds NNs to represent a learned part of dynamics or a control policy. To this end, incremental correction methods are developed for post-processing of the dynamical systems modelled with NNs for which the parameters are determined by previous optimisation process. The proposed approach is to find a small amount of local correction needed to satisfy given state constraints with the updated solution. Algorithms for updating the neural network parameters and the control function are considered.
Amato D, Vallado DA, 2022, Improving long-term special perturbations efficiency for Low Earth Orbits, 5th International Workshop on Key Topics in Orbit Propagation Applied to Space Situational Awareness
Hallgarten La Casta M, Sánchez Fernandez-Mellado L, Amato D, et al., 2022, Non-linear Set Propagation with Generalised Equinoctial Orbital Elements, 5th International Workshop on Key Topics in Orbit Propagation Applied to Space Situational Awareness
Fuentes Muñoz O, Pedrós Faura A, Amato D, et al., 2022, On the prediction of keyholes by propagation of the MOID, Apophis T-7 years: Knowledge Opportunities for the Science of Planetary Defense
In this work we study the variation of the MOID between encounters so that we can determine the keyholes that exist in the B-plane. We compare the different methods to propagate the orbits of asteroids between planetary close encounters.
Hallgarten La Casta M, Amato D, Vasile M, 2022, Polynomial Algebra for Uncertainty Propagation in Generalised Equinoctial Orbital Elements, 73rd International Astronautical Congress
César Daniel E, Amato D, 2022, Lightcurve inversion through LSTMs, International Conference on Computational Science 2022
Araya IA, Amato D, 2022, Spectral analysis of US Space Catalog ephemerides for LAGEOS-1, AIAA SCITECH 2022 Forum, Publisher: American Institute of Aeronautics and Astronautics, Pages: 1-11
The US Space Catalog is the primary source of public ephemeris data on Resident Space Objects. Catalog ephemerides are published as Two-Line Elements (TLEs) which were originally defined as singly-averaged elements according to the Simplified General Perturbations 4 (SGP4) theory. Recently, TLEs have been derived through numerical fits to underlying special perturbations solutions. We conjecture that the numerical fit results in short-periodic terms being embedded in TLEs, and analyse the amplitude spectrum of piecewise continuous osculating solutions derived from TLE sequences for the LAGEOS-1 satellite. The orbital elements spectra contain short-periodic terms at frequencies larger than those reconstructed by the SGP4 theory, which supports the conjecture. For LAGEOS-1, short-periodic terms in addition to those already considered by SGP4 should not be added to TLEs in an effort to improve their accuracy, as they are likely to have been already partially embedded in the TLEs.
Amato D, McMahon JW, 2021, Deep learning method for Martian atmosphere reconstruction, Journal of Aerospace Information Systems, Vol: 18, Pages: 1-1, ISSN: 2327-3097
The reconstruction of atmospheric properties encountered during Mars entry trajectories is a crucial element of postflight mission analysis. This paper proposes a deep learning architecture using a long short-term memory (LSTM) network for the reconstruction of Martian density and wind profiles from inertial measurements and guidance commands. The LSTM is trained on a large set of Mars entry trajectories controlled through the fully numerical predictor-corrector entry guidance (FNPEG) algorithm, with density and wind from the Mars Global Reference Atmospheric Model (GRAM) 2010. The training of the network is examined, ensuring that the LSTM generalizes well to samples not present in the training set, and the performance of the network is assessed on a separate training set. The errors of the reconstructed density and wind profiles are, respectively, within 0.54 and 1.9%. Larger wind errors take place at high altitudes due to the decreased sensitivity of the trajectory in regions of low dynamic pressure. The LSTM architecture reliably reproduces the atmospheric density and wind encountered during descent.
Fuentes-Muñoz O, Pedros-Faura A, Amato D, 2021, Effect of non-Keplerian MOID evolution on preliminary keyhole analyses, 7th IAA Planetary Defense Conference
Bombardelli C, Falco G, Amato D, et al., 2021, Space occupancy in low-earth orbit, Journal of Guidance, Control, and Dynamics: devoted to the technology of dynamics and control, Vol: 44, Pages: 684-700, ISSN: 0731-5090
With the upcoming launch of large constellations of satellites in the low-Earth orbit (LEO) region, it will become important to organize the physical space occupied by the different operating satellites in order to minimize critical conjunctions and avoid collisions. This paper introduces the definition of space occupancy as the domain occupied by an individual satellite as it moves along its nominal orbit under the effects of environmental perturbations throughout a given interval of time. After showing that space occupancy for the zonal problem is intimately linked to the concept of frozen orbits and proper eccentricity, frozen orbit initial conditions are provided in osculating element space and a frozen-orbit polar equation is obtained to describe the space occupancy region in closed analytical form. Next, the problem of minimizing space occupancy is analyzed in a realistic model including tesseral harmonics, third-body perturbations, solar radiation pressure, and drag. The corresponding initial conditions, leading to minimum space occupancy (MiSO) orbits, are obtained numerically for a set of representative configurations in LEO. The implications for the use of MiSO orbits to optimize the design of mega-constellations are discussed.
Fuentes-Muñoz O, Pedros-Faura A, Amato D, 2021, Effect of non-Keplerian MOID evolution on preliminary keyhole analyses, 7th IAA Planetary Defense Conference – PDC 2021
Amato D, Hume S, Roelke E, et al., 2020, Deep learning atmospheric prediction algorithm for enhanced Mars EDL guidance, International Symposium on Artificial Intelligence, Robotics, and Automation in Space
Uncertainty in atmospheric density and wind is a major cause of suboptimalperformance in the Entry, Descent, and Landing (EDL) guidance at Mars. We improve the robustness of current EDL guidance algorithms to uncertain dynamic environments by proposing a reliable on-board atmospheric estimation algorithm. The algorithm consists of a deep, recurrent neural network using an efficient architecture for time-series predictions, the Long Short-Term Memory (LSTM) cell. The LSTM network is trained on entry trajectories simulated with the Fully Numerical Predictor-corrector Guidance (FNPEG); in each trajectory the vehicle is subject to density and wind fields from instances of the Mars Global Reference Atmospheric Model (GRAM) 2010. Predictions of density and wind as a function of altitude expected along the trajectory are obtained from onboard acceleration measurements and state estimates. The algorithm achieves a RMS value over time for the relative density error in the order of 10 % for samples in the validation dataset, and significantly improves performance with respect to an exponential fit to the density.
Amato D, McMahon JW, 2020, Deep learning method for Martian atmosphere reconstruction
Amato D, Hume S, Grace B, et al., 2020, Mars EDL and aerocapture guidance under dynamic uncertainty, AAS/AIAA Astrodynamics Specialist Conference
Amato D, Malhotra R, Sidorenko V, et al., 2020, Lunar close encounters compete with the circumterrestrial Lidov–Kozai effect, Celestial Mechanics and Dynamical Astronomy, Vol: 132, Pages: 1-18, ISSN: 0008-8714
Luna 3 (or Lunik 3 in Russian sources) was the first spacecraft to perform a flyby of the Moon. Launched in October 1959 on a translunar trajectory with large semimajor axis and eccentricity, it collided with the Earth in late March 1960. The short, 6-month dynamical lifetime has often been explained through an increase in eccentricity due to the Lidov–Kozai effect. However, the classical Lidov–Kozai solution is only valid in the limit of small semi-major axis ratio, a condition that is satisfied only for solar (but not for lunar) perturbations. We undertook a study of the dynamics of Luna 3 with the aim of assessing the principal mechanisms affecting its evolution. We analyze the Luna 3 trajectory by generating accurate osculating solutions, and by comparing them to integrations of singly and doubly averaged equations of motion in vectorial form. Lunar close encounters, which cannot be reproduced in an averaging approach, decisively affect the trajectory and break the doubly averaged dynamics. Solar perturbations induce oscillations of intermediate period that affect the geometry of the close encounters and cause the singly averaged and osculating inclinations to change quadrants (the orbital plane “flips”). We find that the peculiar evolution of Luna 3 can only be explained by taking into account lunar close encounters and intermediate-period terms; such terms are averaged out in the Lidov–Kozai solution, which is not adequate to describe translunar or cislunar trajectories. Understanding the limits of the Lidov–Kozai solution is of particular significance for the motion of objects in the Earth–Moon environment and of exoplanetary systems.
Amato D, Hume S, Grace B, et al., 2020, Robustifying Mars descent guidance through neural networks, AAS Guidance, Navigation, and Control Conference
Amato D, Bombardelli C, Baù G, et al., 2019, Non-averaged regularized formulations as an alternative to semi-analytical orbit propagation methods, Celestial Mechanics and Dynamical Astronomy, Vol: 131, Pages: 21-21, ISSN: 1572-9478
Amato D, Bombardelli C, Dell’Elce L, et al., 2019, Recovering the chaotic orbit of Cosmos 862, Toulouse, France
Amato D, Furfaro R, Rosengren AJ, et al., 2018, Attitude propagation of Resident Space Objects with Recurrent Neural Networks, Maui, HI, United States
Amato D, Rosengren AJ, Bombardelli C, 2018, THALASSA: a fast orbit propagator for near-Earth and cislunar space, Kissimmee, Florida, Publisher: American Institute of Aeronautics and Astronautics
Amato D, Rosengren AJ, Baù G, 2018, What Happened to Luna-3? A Numerical Exploration of Cislunar Dynamics, College Station, Texas, USA
Rosengren AJ, Amato D, Bombardelli C, et al., 2018, Resident space object proper orbital elements, Maui, Hawaii, USA
Amato D, Baù G, Bombardelli C, 2017, Accurate orbit propagation in the presence of planetary close encounters, Monthly Notices of the Royal Astronomical Society, Vol: 470, Pages: 2079-2099, ISSN: 0035-8711
Abstract. We present an efficient strategy for the numerical propagation of small Solar system objects undergoing close encounters with massive bodies. The tra
Hernando-Ayuso J, Amato D, Bombardelli C, 2017, Last-minute semi-analytical asteroid deflection by nuclear explosion, Tokyo, Japan
Amato D, 2017, Advanced orbit propagation methods applied to asteroids and space debris
Amato D, Bombardelli C, Baù G, 2016, Efficient numerical propagation of planetary close encounters with regularized element methods, 6th International Conference on Astrodynamics Tools and Techniques (ICATT 2016)
Close encounters with major Solar System bodies may bring about a strong amplification of numerical error during inter-planetary orbit propagation. In this work, we reduce global numerical error by integrating regularized equations of motion instead of the classical Newtonian equations in Cartesian coordinates. The integration performance of several sets ofregularized equations is assessed from large-scale numeri-cal propagations of close encounters in the Sun-Earth planar CR3BP. An essential device consists in switching between primary bodies during the propagation, which effectively decomposes a strongly-perturbed heliocentric problem into two weakly-perturbed ones; this propagation approach has been dubbed Online Trajectory Matching (OTM). Through this simple expedient, regularized equations describing the evolution of non-classical orbital elements achieve excellent performances compared to Newtonian equations, even when employing sophisticated adaptive numerical schemes.Further improvements might be expected by carefully selecting the location of the switch of primary bodies during the propagation.
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