1,721,063 research outputs found
L-BAND SAR Applications and Requirements Consolidation Study
No full textIl progetto prevede l’esecuzione di una ricerca concernente la definizione di prodotti di una missione satellitare SAR in banda L che dovrà costituire un nuovo elemento del programma Copernicus. La ricerca riguarderà la definizione dei prodotti batimetrici della missione satellitare SAR in banda L. Il programma della ricerca è articolato in una serie di attività finalizzate a i) individuare i requisiti utente in ambito batimetrico, ii) trasformare i requisiti utente in requisiti di prodotto SAR, iii) trasferire i requisiti di prodotto in specifiche di sistema
Definizione e sviluppo di modelli di calcolo da utilizzare per l'analisi ed il dimensionamento di strumenti radar ad apertura sintetica (SAR) frammentati, basati su configurazioni di tipo Bistatico (un trasmettitore ed un ricevitore piazzati su satelliti distinti) o Multistatico (un trasmettitore e ricevitori multipli piazzati su satelliti distinti
No full textCrater-based Autonomous Position Estimation in Planetary Missions by Deep-Learning
No full textSpacecraft missions venturing beyond Earth rely upon ranging, specific payloads or supports systems, claiming the usage of facilities such as Deep Space Network or ESTRACK. This requires a significant amount of resources both on Earth and onboard, especially in monetary terms. Furthermore, satellite link is not always guaranteed, and results are not available in real-time. Therefore, to cruise independently of Earth-based operators and to achieve the requirements raised by the next planetary exploratory missions, this manuscript proposes a novel visual-based terrain relative navigation (TRN) system. TRN is promising because can be applied to a wide range of space missions, e.g. planetary exploration (rocky planets), the study of moons of gaseous planets, approach phase of comets, asteroid, and other celestial bodies. In essence, a spacecraft can retrieve its absolute position by matching a pattern of observed craters with a database. The measurements thus obtained can be integrated into a navigation filter to estimate the spacecraft state (position and velocity). The ability to detect match surface features to a map is crucial for TRN. However, craters largely vary their appearances also depending on image qualities, lighting geometry, and noises. For these reasons, realizing a crater detector able to generalize to different scenarios is complex. It is worth considering that this task must be performed in a robust way to keep high the navigation accuracy. In past, this has led to least square approaches, creating situations where corrupted navigation states render otherwise good images ineffectual, leading to unnecessary filter reinitializations, trajectory aborts (e.g. during lunar descent), or other undesirable events. Contrarily, the solution proposed is reliable, combining the strengths of a region-based convolutional neural network (Mask R-CNN) with the robustness of projective invariants theory. An extended Kalman filter completes the TRN system, further increasing the stability of the system. Despite the usage of medium resolution (118 m/px) data, results showed that the navigation accuracy lies below 400 meters in the best-case scenario for a satellite orbiting around the Moon at about 50 km altitude. This is expected to guarantee real-time autonomous onboard operations with no need for ground support
Ionospheric path delay models for spaceborne GPS receivers flying in formation with large baselines
Full text linkGPS relative navigation filters could benefit notably from an accurate modeling of the ionospheric delays, especially over large baselines (>100 km) where double difference delays can be higher than several carrier wavelengths. This paper analyzes the capability of ionospheric path delay models proposed for spaceborne GPS receivers in predicting both zero-difference and double difference ionospheric delays. We specifically refer to relatively simple ionospheric models, which are suitable for real-time filtering schemes. Specifically, two ionospheric delay models are evaluated, one assuming an isotropic electron density and the other considering the effect on the electron density of the Sun aspect angle. The prediction capability of these models is investigated by comparing predicted ionospheric delays with measured ones on real flight data from the Gravity Recovery and Climate Experiment mission, in which two satellites fly separated of more than 200 km. Results demonstrate that both models exhibit a correlation in the excess of 80% between predicted and measured double-difference ionospheric delays. Despite its higher simplicity, the isotropic model performs better than the model including the Sun effect, being able to predict double differenced delays with accuracy smaller than the carrier wavelength in most cases. The model is thus fit for supporting integer ambiguity fixing in real-time filters for relative navigation over large baselines. Concerning zero-difference ionospheric delays, results demonstrate that delays predicted by the isotropic model are highly correlated (around 90%) with those estimated using GPS measurements. However, the difference between predicted and measured delays has a root mean square error in the excess of 30 cm. Thus, the zero-difference ionospheric delays model is not likely to be an alternative to methods exploiting carrier-phase observables for cancelling out the ionosphere contribution in single-frequency absolute navigation filters
Formation Flying SAR: analysis of imaging performance by Array Theory
No full textThis paper analyzes the process of image synthesis for a Formation Flying Synthetic Aperture Radar (FF-SAR), which is a multistatic Synthetic Aperture Radar (SAR) based on a cluster of receiving-only satellites flying in a close formation, in the framework of the array theory. Indeed, the imaging properties of different close receivers, when analyzed as isolated items, are very similar and form the so-called common array. Moreover, the relative positions among the receivers implicitly define a physical array, referred to as spatial diversity array. FF-SAR imaging can be verified as a result of the spatial diversity array weighting the common array. Hence, different approaches to beamforming can be applied to the spatial diversity array to provide the FF-SAR with distinctive capabilities, such as coherent resolution enhancement and high-resolution wideswath imaging. Simulation examples are discussed which confirm that array theory is a powerful tool to quickly and easily characterize FF-SAR imaging performance
A Deep Learning-based Crater Detector for Autonomous Vision-Based Spacecraft Navigation
No full textThe paper proposes the use of Cascade Mask R-CNN for the detection of craters from monocular images. Crater detection is a challenging task being the images prone to changes in lighting and noise conditions. Besides, the crater appearance is strongly modified according to the region of interest, being the shadows strongly affected by the sun vector inclination. To tackle these issues, the paper exploits the generalizability of modern deep learning architectures to create a highly reliable crater detector. The dataset used for transfer learning the model comprises more than 800 real lunar monocular images obtained from the lunar reconnaissance orbiter (LRO) cameras. Results confirm the performance reached by the multi-stage object detection architecture both in equatorial and polar regions, its robustness, and the validity of this crater detection scheme for planetary navigation tasks
Above Ground Biomass Estimation in Agroforestry Environment by UAS and RGB Imagery
No full textRapid advances in unmanned aerial system (UAS) platforms have boosted the use of low-altitude aerial imagery in estimating crops Above Ground Biomass (AGB). By electro-optical camera onboard UAS it is easy to obtain crop information at the farm scale under adequate weather conditions with high temporal and spatial resolution. In order to assess the biomass of woody crops, this study intends to evaluate the potential of Red Green Blue (RGB)-imagery and of the relevant vegetation indices to compute diameter at breast height and plant height as the main input for AGB estimation. The method monitors the biomass, carbon stock, and coverage of tree plants by integrating various techniques and software. It is also of general validity, so it can apply to other woody crops and results may help managers of ecosystem assess and monitor ecosystems as well as remediation and revegetation initiatives
Relative navigation in LEO by carrier-phase differential GPS with intersatellite ranging augmentation
No full textCarrier-phase differential GPS (CDGPS) is a promising technology for accurate relative navigation in LEO formations of cooperating satellites, but navigation filter robustness against poor GPS geometry and noisy measurements has to be improved. This can be performed by augmenting the navigation filter with intersatellite local ranging measurements, as the ones provided by ranging transponders or GNSS-like systems. In this paper, an augmented CDGPS navigation filter is proposed for the formation of two satellites characterized by a short, varying baseline, relevant to next generation Synthetic Aperture Radar missions. Specifically, a cascade-combination of dynamic and kinematic filters which processes double-differenced code and carrier measurements on two frequencies, as well as local inter-satellite ranging measurements, is used to get centimeter-level baseline estimates. The augmented filter is validated by numerical simulations of the formation orbital path. Results demonstrate that the proposed approach is effective in preserving the centimeter-level accuracy achievable by a CDGPS-only filter also in the presence of a poor GDOP or a limited number of GPS satellites in view. © 2013 Alfredo Renga et al
Earth observation with MEO transmitters and UAS receivers: a potential utilization of Galileo constellation
No full textBeamforming performance characterization for a Distributed SAR in a long baseline bistatic configuration
No full textDistributed Synthetic Aperture Radar (DSAR) enables high-quality images generation exploiting multiple smaller satellites, so it represents a promising concept for future space missions. When a long baseline between the transmitter and the receivers is realized, additional information about the scene could be retrieved due to the bistatic observation geometry, but standard methods to predict beamforming performance cannot be used. In this paper, two different techniques able to deal with the long baseline bistatic case are introduced and validated in a dedicated simulation environment
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