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Martin-Escalona I.,Polytechnic University of Catalonia | Barcelo-Arroyo F.,Polytechnic University of Catalonia | Ciurana M.,Aerospace Research and Technology Center
2010 International Congress on Ultra Modern Telecommunications and Control Systems and Workshops, ICUMT 2010 | Year: 2010

Ad hoc networks are becoming increasingly relevant in positioning solutions, mainly due to the capabilities of current portable devices and the collaborative nature of such networks, which can improve some of the limitations of the positioning solutions in regular wireless networks. Scalability and accuracy are the most constraining factors of a location algorithm for ad hoc networks. This paper presents an algorithm for passive location in ad hoc networks. This algorithm uses the location traffic in the network to compute the position of the nodes. This passive behavior makes this solution ideal for scalability because one single active node can locate as many nodes as it can cover in the network. This paper provides a definition for the algorithm and explores the expected accuracy of passive positions. ©2010 IEEE.


Fernandez D.,Polytechnic University of Catalonia | Barcelo-Arroyo F.,Polytechnic University of Catalonia | Martin-Escalona I.,Polytechnic University of Catalonia | Ciurana M.,Aerospace Research and Technology Center | And 2 more authors.
Proceedings - IEEE Symposium on Computers and Communications | Year: 2011

This paper proposes a positioning method that combines GPS pseudoranges and WLAN ranges when less than four GPS satellites are within sight. To enhance the positioning availability, a tight hybridization approach with both technologies is considered. Although the work has been performed considering WLAN and GPS, most of the presented ideas, procedures and results are also valid for generic tight non-synchronized fusion of GNSS with terrestrial signals [1]. Special emphasis is placed on the phenomenon of positioning ambiguity that appears due to the combination of measurements with different characteristics. To solve this ambiguity, a method is proposed and studied. The availability and accuracy of the system are tested considering different satellite and terrestrial geometries. The results show that the proposed system is able to improve the availability while maintaining the accuracy of GPS as a standalone. © 2011 IEEE.


Hedjazi L.,Roche Holding AG | Hedjazi L.,National Polytechnic Institute of Toulouse | Aguilar-Martin J.,Aerospace Research and Technology Center | Le Lann M.-V.,Roche Holding AG | Le Lann M.-V.,National Polytechnic Institute of Toulouse
Pattern Recognition Letters | Year: 2011

In this paper we propose a feature selection method for symbolic interval data based on similarity margin. In this method, classes are parameterized by an interval prototype based on an appropriate learning process. A similarity measure is defined in order to estimate the similarity between the interval feature value and each class prototype. Then, a similarity margin concept has been introduced. The heuristic search is avoided by optimizing an objective function to evaluate the importance (weight) of each interval feature in a similarity margin framework. The experimental results show that the proposed method selects meaningful features for interval data. In particular, the method we propose yields a significant improvement on classification task of three real-world datasets. © 2010 Elsevier B.V. All rights reserved.


Bravo C.,Halliburton Co. | Saputelli L.,Hess Corporation | Castro J.A.,Hess Corporation | Rios A.,University of Los Andes, Colombia | And 2 more authors.
Society of Petroleum Engineers - SPE Digital Energy Conference and Exhibition 2011 | Year: 2011

Integrated Asset Management (IAM) is highly complex and requires the combined effort of several disciplines and technological tools. The orchestration of disciplines, workflow tools, and available data are paramount issues in the oil and gas industry today. Resource negotiation, communication language, and decision-making protocols are minor issues that exacerbate the problem, resulting in poor and delayed decision making. This study approaches these challenges through the implementation of innovative, distributed artificial intelligence (AI)-based architecture, designed for automated production management. This architecture, known as the Integrated Production Management Architecture (IPMA), has three layers: a connectivity layer, which allows access to the process information sources; a semantic layer, which establishes an ontological framework to guarantee the process-information integrity during the data interchange process developed between the applications that belong to the Enterprise Technology Information Platform; and a management layer, which automates the production process workflows using oilfield multi-agent systems and electronic institutions. A virtual oilfield, based on a commercial-integrated production model (IPM) and history-matched data, was used to show the benefits of the proposed approach. The IPM had the following configuration: Three reservoirs, eight oil wells, one flow station, and several gathering pipelines. The IPMA's objective was to maximize asset revenue under different constraint scenarios and changing operational events. The reactive capacity of the architecture, the effective communication between the agents, and the proposed oilfield ontology were tested successfully. In this sense, the well function of the three layers of IPMA was demonstrated. This study also outlines the use of ontologies and AI techniques that are important factors in future developments of IT solutions for the oil production industry. Copyright 2011, Society of Petroleum Engineers.


Lyamine H.,Roche Holding AG | Lyamine H.,Toulouse 1 University Capitole | Aguilar-Martin J.,Aerospace Research and Technology Center | Le Lann M.-V.,Roche Holding AG | And 3 more authors.
International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems | Year: 2012

Human knowledge about monitoring process variables is usually incomplete. To deal with this partial knowledge many types of representation other than the quantitative one are used to describe process variables (qualitative, symbolic interval). Thus, the development of automatic reasoning mechanisms about the process is faced with this problem of multiple data representations. In this paper, a unified principle for reasoning about heterogeneous data is introduced. This principle is based on a simultaneous mapping of data from initially heterogeneous spaces into only one homogeneous space based on a relative measure using appropriate characteristic functions. Once the heterogeneous data are represented in a unified space, a single processing for various analysis purposes can be performed using simple reasoning mechanisms. An application of this principle within a fuzzy logic framework is performed here to demonstrate its effectiveness. We show that simple fuzzy reasoning mechanisms can be used to reason in a unified way about heterogeneous data in three well known machine learning problems. © 2012 World Scientific Publishing Company.


Sun J.,Aerospace Research and Technology Center | Xhafa F.,University of Barcelona
Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2011 | Year: 2011

In this paper we address the resolution of the Ground Station Scheduling problem by Genetic Algorithms. Ground Stations (GS) are required during spacecraft (S/C) operations to provide communications links between operations teams and the S/C systems. Basic communication types, such as telemetry, tele-command and tracking, are all supported by the same satellite and GS systems. The allocation of ground resources to S/C is a highly constrained problem and traditionally has been conducted manually: stations are selected for communication support with certain S/C for certain periods. The manual approach has clear limitations and new modern scheduling approaches are needed to tackle with the complexity of the problem and produce optimal solutions to scheduling operations. We propose the use of Genetic Algorithm, a well-known family of population-based methods, for solving the problem. A series of genetic operators have been designed to find the configuration that outputs the best GA solution for the problem. The proposed GA has been implemented in Matlab and experimentally studied on a set of randomly generated instances. The results of the study showed the effectiveness of the proposed GA algorithm. © 2011 IEEE.


Tappero F.,Aerospace Research and Technology Center | Merminod B.,Ecole Polytechnique Federale de Lausanne | Ciurana M.,Aerospace Research and Technology Center
2010 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2010 - Conference Proceedings | Year: 2010

The implementation of a ranging exploitation method over the IEEE 802.11 signal standard for a software-defined radio architecture is presented. We propose the current wireless local access network (WLAN) as standard assistive infrastructure for ubiquitous localisation and positioning. The paper describes the architecture of a localisation receiver built around a FPGA. The described receiver can ideally process GNSS signals, available for any number of satellites, together with IEEE 802.11 signals available from surrounding WLAN access points to infer its own position. WLAN AP visibility, expected positioning accuracy and global service coverage over a large university campus are discussed. The IEEE 802.11 ranging method and its implementation in a single software-defined receiver are discussed. © 2010 IEEE.


Blanco-Delgado N.,Aerospace Research and Technology Center
GIM International | Year: 2011

The use of high-precision GPS for surveying applications has increased dramatically over the last decade. GPS receivers can provide high accuracy and rapid results, saving enormous amounts of time by covering large areas in a short time. While there have been some developments that have produced high-accuracy, real-time solutions with single-frequency receivers, the appearance of new signals and constellations is now making it possible to use two frequencies less expensively. Scientists have long discussed the potential of new signals for multi-frequency, multi-GNSS applications and have expressed a great interest in signal combinations, particularly those of carrier-phase measurements, involving multiple frequencies simultaneously. The use of triple-frequency combinations has, for example, been demonstrated to be of great interest for ambiguity resolution in precise carrier-phase-based positioning, for receiver autonomous integrity monitoring, and for ionospheric research. With 27 satellites in orbit and 23 operational satellites, GLONASS provides almost global coverage.


Gutierrez E.,Aerospace Research and Technology Center | Quintana M.,Aerospace Research and Technology Center | Chester E.,Aerospace Research and Technology Center
IFAC Proceedings Volumes (IFAC-PapersOnline) | Year: 2010

In this paper we investigate new schemes to improve the operability of heterogeneous Unmanned Aircraft Systems (UAS) teams through the exploitation of inter-vehicular communications. Releasing ground links from unnecessary data exchanges saves resources and alleviates the inherent scalability problem resulting from the increase in the number of UAS to be controlled simultaneously. An architecture based on an aerial Mobile Ad-hoc Network (MANET) is proposed for the management of the data exchange among all the vehicles in the team. A performance evaluation of the two most relevant MANET approaches for path discovery (namely, reactive and proactive) has been carried out by means of simulation of two well-known routing protocols: Ad-hoc On-demand Distance Vector (AODV) and Destination Sequenced Distance Vector (DSDV). Several network configurations are generated to emulate different possible contingencies that might occur in real UAS team operations. Network topology evolution, vehicle flight dynamics and data traffic patterns are considered as input parameters to the simulation model. The analysis of the system behavior for each possible network configuration is used to evaluate the appropriateness of both approaches in different mission scenarios. Finally, an assessment of the simulation results is presented along with a discussion about further research challenges.


Gutierrez E.,Aerospace Research and Technology Center | Lopez-Salcedo J.A.,Autonomous University of Barcelona | Seco-Granados G.,Autonomous University of Barcelona
2011 8th International Workshop on Multi-Carrier Systems and Solutions, MC-SS 2011 | Year: 2011

The design of efficient architectures for Multi-Carrier (MC) communication systems can be a challenging task when it involves the adoption of Filter-Bank Multi-Carrier (FBMC) modulation techniques. The main design issues found in FBMC systems are generated by the incorporation of band-limited shaping pulses. Yet, these pulses have many advantages in terms of performance, such as providing either improved spectral confinement or no frequency overlap between adjacent subcarriers. They also benefit from robustness in front of narrowband interferences, and reduced out-of-band power emission, among others. However, the advantages of FBMC schemes are often obscured when it comes to the implementation point of view. This is particularly true for the flexible FBMC systems, where on top of incorporating band-limited shaping pulses, no restrictions are imposed on the signal parameters (i.e. symbol rate, carrier spacing or sampling frequency). In this context, the present paper will provide a unified framework to describe flexible FBMC signals when both signal design and implementation criteria are combined. © 2011 IEEE.

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