Numerical solutions for lunar orbits

Starting from a variational formulation based on Hamilton’s Principle, the paper exploits the finite element technique in the time domain in order to solve orbital dynamic problems characterised by constrained boundary value rather than initial value problems. The solution is obtained assembling a suitable number of finite elements inside the time interval of interest, imposing the desired constraints, and solving the resultant set of non-linear algebraic equations by means of Newton-Raphson method. In particular, in this work this general solution strategy is applied to periodic orbits determination. The effectiveness of the approach in finding periodic orbits in the unhomogeneous gravity field of the Moon is assessed by means of relevant examples, and the results are compared with those obtained by standard time marching techniques as well as with analytical results

Direct lunar descent optimisation by finite elements in time approach

In this paper a direct approach to trajectory optimisation, based on Finite Elements in Time (FET) discretisation is presented. Trajectory optimisation is performed combining the effectiveness and flexibility of Finite Elements in Time in solving complex boundary values problems with a common nonlinear programming algorithm. In order to avoid low accuracy proper to direct approaches, a mesh adaptivity strategy is implemented which exploits the ability of finite elements to represent both continuous and discontinuous functions. The effectiveness and accuracy of direct transcription by FET are proved by a selected number of sample problems. Finally an optimal landing manoeuvre is presented to show the power of the proposed approach in solving even complex and realistic problems

Testing approaches for global optimization of space trajectories

In this paper the procedures to test global search algorithms applied to space trajectory design problems are discussed. Furthermore, a number of performance indexes that can be used to evaluate the effectiveness of the tested algorithms are presented. The performance indexes are then compared and the actual significance of each one of them is highlighted. Three global optimization algorithms are tested on three typical space trajectory design problems

On testing global optimization algorithms for space trajectory design

In this paper we discuss the procedures to test a global search algorithm applied to a space trajectory design problem. Then, we present some performance indexes that can be used to evaluate the effectiveness of global optimization algorithms. The performance indexes are then compared highlighting the actual significance of each one of them. A number of global optimization algorithms are tested on four typical space trajectory design problems. From the results of the proposed testing procedure we infer for each pair algorithm-problem the relation between the heuristics implemented in the solution algorithm and the main characteristics of the problem under investigation. From this analysis we derive a novel interpretation of some evolutionary heuristics, based on dynamical system theory and we significantly improve the performance of one of the tested algorithms

An automatic technique for visual quality classification for MPEG-1 video

The Centre for Digital Video Processing at Dublin City University developed Fischlar [1], a web-based system for recording, analysis, browsing and playback of digitally captured television programs. One major issue for Fischlar is the automatic evaluation of video quality in order to avoid processing and storage of corrupted data. In this paper we propose an automatic classification technique that detects the video content quality in order to provide a decision criterion for the processing and storage stages

Local wavelet features for statistical object classification and localisation

This article presents a system for texture-based probabilistic classification and localisation of 3D objects in 2D digital images and discusses selected applications. The objects are described by local feature vectors computed using the wavelet transform. In the training phase, object features are statistically modelled as normal density functions. In the recognition phase, a maximisation algorithm compares the learned density functions with the feature vectors extracted from a real scene and yields the classes and poses of objects found in it. Experiments carried out on a real dataset of over 40000 images demonstrate the robustness of the system in terms of classification and localisation accuracy. Finally, two important application scenarios are discussed, namely classification of museum artefacts and classification of metallography images

Associating low-level features with semantic concepts using video objects and relevance feedback

The holy grail of multimedia indexing and retrieval is developing algorithms capable of imitating human abilities in distinguishing and recognising semantic concepts within the content, so that retrieval can be based on ”real world” concepts that come naturally to users. In this paper, we discuss an approach to using segmented video objects as the midlevel connection between low-level features and semantic concept description. In this paper, we consider a video object as a particular instance of a semantic concept and we model the semantic concept as an average representation of its instances. A system supporting object-based search through a test corpus is presented that allows matching presegmented objects based on automatically extracted lowlevel features. In the system, relevance feedback is employed to drive the learning of the semantic model during a regular search process

Extension of the sun-synchronous Orbit

Through careful consideration of the orbit perturbation force due to the oblate nature of the primary body a secular variation of the ascending node angle of a near-polar orbit can be induced without expulsion of propellant. Resultantly, the orbit perturbations can be used to maintain the orbit plane in, for example, a near-perpendicular (or at any other angle) alignment to the Sun-line throughout the full year of the primary body; such orbits are normally termed Sun-synchronous orbits [1, 2]. Sun-synchronous orbits about the Earth are typically near-circular Low-Earth Orbits (LEOs), with an altitude of less than 1500 km. It is normal to design a LEO such that the orbit period is synchronised with the rotation of the Earth‟s surface over a given period, such that a repeating ground-track is established. A repeating ground-track, together with the near-constant illumination conditions of the ground-track when observed from a Sun-synchronous orbit, enables repeat observations of a target over an extended period under similar illumination conditions [1, 2]. For this reason, Sun-synchronous orbits are extensively used by Earth Observation (EO) platforms, including currently the Environmental Satellite (ENVISAT), the second European Remote Sensing satellite (ERS-2) and many more. By definition, a given Sun-synchronous orbit is a finite resource similar to a geostationary orbit. A typical characterising parameter of a Sun-synchronous orbit is the Mean Local Solar Time (MLST) at descending node, with a value of 1030 hours typical. Note that ERS-1 and ERS-2 used a MLST at descending node of 1030 hours ± 5 minutes, while ENVISAT uses a 1000 hours ± 5 minutes MLST at descending node [3]. Following selection of the MLST at descending node and for a given desired repeat ground-track, the orbit period and hence the semi-major axis are fixed, thereafter assuming a circular orbit is desired it is found that only a single orbit inclination will enable a Sun-synchronous orbit [2]. As such, only a few spacecraft can populate a given repeat ground-track Sun-synchronous orbit without compromise, for example on the MLST at descending node. Indeed a notable feature of on-going studies by the ENVISAT Post launch Support Office is the desire to ensure sufficient propellant remains at end-of-mission for re-orbiting to a graveyard orbit to ensure the orbital slot is available for future missions [4]. An extension to the Sun-synchronous orbit is considered using an undefined, non-orientation constrained, low-thrust propulsion system. Initially the low-thrust propulsion system will be considered for the free selection of orbit inclination and altitude while maintaining the Sun-synchronous condition. Subsequently the maintenance of a given Sun-synchronous repeat-ground track will be considered, using the low-thrust propulsion system to enable the free selection of orbit altitude. An analytical expression will be developed to describe these extensions prior to then validating the analytical expressions within a numerical simulation of a spacecraft orbit. Finally, an analysis will be presented on transfer and injection trajectories to these orbits

QIMERA: a software platform for video object segmentation and tracking

In this paper we present an overview of an ongoing collaborative project in the field of video object segmentation and tracking. The objective of the project is to develop a flexible modular software architecture that can be used as test-bed for segmentation algorithms. The background to the project is described, as is the first version of the software system itself. Some sample results for the first segmentation algorithm developed using the system are presented and directions for future work are discussed

Using video objects and relevance feedback in video retrieval

Video retrieval is mostly based on using text from dialogue and this remains the most signi¯cant component, despite progress in other aspects. One problem with this is when a searcher wants to locate video based on what is appearing in the video rather than what is being spoken about. Alternatives such as automatically-detected features and image-based keyframe matching can be used, though these still need further improvement in quality. One other modality for video retrieval is based on segmenting objects from video and allowing end users to use these as part of querying. This uses similarity between query objects and objects from video, and in theory allows retrieval based on what is actually appearing on-screen. The main hurdles to greater use of this are the overhead of object segmentation on large amounts of video and the issue of whether we can actually achieve effective object-based retrieval. We describe a system to support object-based video retrieval where a user selects example video objects as part of the query. During a search a user builds up a set of these which are matched against objects previously segmented from a video library. This match is based on MPEG-7 Dominant Colour, Shape Compaction and Texture Browsing descriptors. We use a user-driven semi-automated segmentation process to segment the video archive which is very accurate and is faster than conventional video annotation