Information Fusion

Three dimensional object extraction and recognition (OER) from LIDAR data has been an area of major interest in photogrammetry for quite a long time. However, most of the existing methods for automatic object extraction and recognition from LIDAR data are just based on the range information and employ parametric methods and object’s vagueness behaviour is basically neglected. Thus, these methods do not take into account the extraction and recognition complexities and may fail to reach a satisfied reliability level in complex situations. In this paper a novel approach based on the following strategies is formulated and implemented: (a) for a more comprehensive definition of the objects, information fusion concept is utilized, i.e., object’s descriptive components such as 3D structural and textural (ST) information are automatically extracted from first/last rang and intensity information of LIDAR data and simultaneously fed into the evaluation process, (b) for a more realistic expres...

Data mining and machine learning technology has been extensively applied in network intrusion detection and prevention systems by discovering user behavior patterns from the network traffic data. Some commercial tools for collecting network traffic data exist, such as SNORT. The ...

In this paper we propose a new algorithm for the detection of clustered microcalcifications using mathematical morphology and artificial neural networks. Mathematical morphology provides tools for the extraction of microcalcifications even if the microcalcifications are located on a non-uniform background Considering each mammogram as a topographic representation, each microcalcification appears as elevation constituting a regional maxima. Morphological filters are applied,

Abstract—This paper provides a theoretical framework for analysis of consensus algorithms for multi-agent networked systems with an emphasis on the role of directed information flow, robustness to changes in network topology due to link/node fail-ures, time-delays, and performance guarantees. An overview of basic concepts of information consensus in networks and methods of convergence and performance analysis for the algorithms are provided. Our analysis framework is based on tools from matrix theory, algebraic graph theory, and control theory. We discuss the connections between consensus problems in networked dynamic systems and diverse applications including synchronization of coupled oscillators, flocking, formation control, fast consensus in small-world networks, Markov processes and gossip-based algorithms, load balancing in networks, rendezvous in space, dis-tributed sensor fusion in sensor networks, and belief propagation. We establish direct connections between spectral and ...

Metadata interoperability is crucial for various kinds of surveillance applications and systems, e.g. metadata mining in multi-sensor environments, metadata exchange in networked camera systems or information fusion in multi-sensor and multi-detector environments. Different metadata formats have been proposed to foster metadata interoperability, but they show significant limitations. ViPER, CVML and MPEG Visual Surveillance MAF support only the visual modality, CVML's

The theoretic fundamentals of distributed information fusion are well developed. However, practical applications of these theoretical results to dynamic sensor networks have remained a challenge. There has been a great deal of work in developing distributed ...

The paper describes manufacturing simulation with a focus on discrete event simulation and computer aided robotics. Some generic good practices, problems, and pitfalls in the use of simulation are described. Some advanced applications of manufacturing simulation are described and elucidated on the hand of a system for simulation-based service & maintenance. Simulation-based decision support and information fusion are closely related, and plans for novel synergistic research in these area are presented.

As the spacefaring community is well aware, the increasingly rapid proliferation of man-made objects in space, whether active satellites or debris, threatens the safe and secure operation of spacecraft and requires that we change the way we conduct business in space. The introduction of appropriate protocols and procedures to regulate the use of space is predicated on the availability of quantifiable and timely information regarding the behavior of resident space objects (RSO): the basis of space domain awareness (SDA). Yet despite five decades of space operations, and a growing global dependence on the services provided by space-based platforms, the population of Earth orbiting space objects is still neither rigorously nor comprehensively quantified, and the behaviors of these objects, whether directed by human agency or governed by interaction with the space environment, are inadequately characterized. Key goals of advanced SDA are to develop a capability to predict RSO behavior, extending SDA beyond its present paradigm of catalog maintenance and forensic analysis, and to arrive at a comprehensive physical understanding of all of the inputs that affect the motion of RSOs. Solutions to these problems require multidisciplinary engagement that combines space surveillance data with other information, including space object databases and space environmental data, to help decision-making processes predict, detect, and quantify threatening and hazardous space domain activity. 1.0 INTRODUCTION This document presents an introductory overview of space surveillance, tracking, and information fusion for SDA. A relevant activity is the NATO Science and Technology Organization's Task Group (SCI-279-TG) is addressing the technical considerations for enabling a NATO-Centric Space Domain Common Operating Picture (COP). The impetus for this effort is the growing dependence by NATO and its member nations on space capabilities to achieve its mission responsibilities as well as the growing role that space, as an operational domain in its own right, is playing in matters concerning global security. NATO has recognized this important reality and increased the Alliance's collective attention on ensuring NATO operations maximize their leverage of space while ensuring the space capabilities provided by its member nations are preserved to the maximum extent possible. A critical element of ensuring the availability and efficacy of these space capabilities is the availability of a common operational perspective or picture of the space domain throughout the Alliance and its partners. The presumption is that NATO forces will be more efficient, protected and successful in their future missions if a common operational perspective can be achieved across all operational domains in which NATO must operate; air, land, sea, cyber AND space. The corollary is, without a common Alliance perspective of the space domain,

For pragmatic information fusion system design and analysis, the user (commander or operator/analyst) needs information in a timely manner to conduct actionable intelligence. With the development of complex information fusion systems, the user still provides valuable inputs to the information fusion system in contextual reasoning and situation understanding. In this paper, we describe the Cognitive Observe-Orient-Decide-Act (C-OODA) model as a method of user and team analysis in the context of the Data Fusion Information Group (DFIG) Information Fusion Model. From the DFIG model [as an update to the Joint Directors of the Lab (JDL) model], we look at Level 5 Fusion of “user refinement” in the context of timely decision making. Using control theory, we present an example of user timeliness assessment in an information fusion decision making model analysis. We model the information input delays in reaching a decision and the action output delays in executing the decision. The C-OODA c...

In emerging cognitive radio (CR) networks, the first cognitive task preceding any dynamic spectrum management is the sensing and identification of spectrum holes in wireless environments. This paper develops a distributed compressed spectrum sensing approach for (ultra-)wideband CR networks. First, compressive sampling is performed at local CRs to scan the very wide spectrum at practical signal-acquisition complexity. Then, measurements or states from multiple CR detectors are fused to collect spatial diversity gain, which improves the detection quality especially under fading channels. Distributed fusion algorithms are derived to effect collaborative fusion at low communication and computation load scalable to the network size. Multiple performance metrics are identified to evaluate the proposed spectrum sensing techniques, as well as to assess those performance-determining factors in system design. Computer simulations corroborate the effectiveness of the proposed techniques in id...

The fourth volume on Advances and Applications of Dezert-Smarandache Theory (DSmT) for information fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics. The contributions (see List of Articles published in this book, at
the end of the volume) have been published or presented after disseminating the third volume (2009, http://fs.gallup.unm.edu/DSmT-book3.pdf) in international conferences, seminars, workshops and journals.