Reconnaissance
2,962 resources related to Reconnaissance
IEEE Organizations related to Reconnaissance
Back to TopConferences related to Reconnaissance
Back to Top2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)
The scope of the 2020 IEEE/ASME AIM includes the following topics: Actuators, Automotive Systems, Bioengineering, Data Storage Systems, Electronic Packaging, Fault Diagnosis, Human-Machine Interfaces, Industry Applications, Information Technology, Intelligent Systems, Machine Vision, Manufacturing, Micro-Electro-Mechanical Systems, Micro/Nano Technology, Modeling and Design, System Identification and Adaptive Control, Motion Control, Vibration and Noise Control, Neural and Fuzzy Control, Opto-Electronic Systems, Optomechatronics, Prototyping, Real-Time and Hardware-in-the-Loop Simulation, Robotics, Sensors, System Integration, Transportation Systems, Smart Materials and Structures, Energy Harvesting and other frontier fields.
2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)
HRI is a highly selective annual conference that showcases the very best research and thinking in human-robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior, anthropology, and many other fields.
For its 20th year edition, the IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) 2019, returns to the country that saw its birth, France. Held in Cannes, in the heart of the world renown “French Riviera” (Cote d’Azur in French), the SPAWC 2019 will exhibit a technical program complete with high profile plenaries, invited and contributed papers, all appearing under IEEE explore. A flagship workshop of the IEEE SP Society SPCOM technical committee, SPAWC 2019 will combine cutting edge research in the fields of signal processing, statistical learning, communication theory, wireless networking and more, together with an exciting social program on the glamorous and sunny Riviera.
2019 IEEE 58th Conference on Decision and Control (CDC)
The CDC is recognized as the premier scientific and engineering conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, systems and control, and related areas.The 58th CDC will feature contributed and invited papers, as well as workshops and may include tutorial sessions.The IEEE CDC is hosted by the IEEE Control Systems Society (CSS) in cooperation with the Society for Industrial and Applied Mathematics (SIAM), the Institute for Operations Research and the Management Sciences (INFORMS), the Japanese Society for Instrument and Control Engineers (SICE), and the European Union Control Association (EUCA).
2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
International Geosicence and Remote Sensing Symposium (IGARSS) is the annual conference sponsored by the IEEE Geoscience and Remote Sensing Society (IEEE GRSS), which is also the flagship event of the society. The topics of IGARSS cover a wide variety of the research on the theory, techniques, and applications of remote sensing in geoscience, which includes: the fundamentals of the interactions electromagnetic waves with environment and target to be observed; the techniques and implementation of remote sensing for imaging and sounding; the analysis, processing and information technology of remote sensing data; the applications of remote sensing in different aspects of earth science; the missions and projects of earth observation satellites and airborne and ground based campaigns. The theme of IGARSS 2019 is “Enviroment and Disasters”, and some emphases will be given on related special topics.
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Periodicals related to Reconnaissance
Back to TopAntennas and Wireless Propagation Letters, IEEE
IEEE Antennas and Wireless Propagation Letters (AWP Letters) will be devoted to the rapid electronic publication of short manuscripts in the technical areas of Antennas and Wireless Propagation.
Applied Superconductivity, IEEE Transactions on
Contains articles on the applications and other relevant technology. Electronic applications include analog and digital circuits employing thin films and active devices such as Josephson junctions. Power applications include magnet design as well asmotors, generators, and power transmission
Automatic Control, IEEE Transactions on
The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...
IEEE Communications Magazine was the number three most-cited journal in telecommunications and the number eighteen cited journal in electrical and electronics engineering in 2004, according to the annual Journal Citation Report (2004 edition) published by the Institute for Scientific Information. Read more at http://www.ieee.org/products/citations.html. This magazine covers all areas of communications such as lightwave telecommunications, high-speed data communications, personal communications ...
Computer, the flagship publication of the IEEE Computer Society, publishes peer-reviewed technical content that covers all aspects of computer science, computer engineering, technology, and applications. Computer is a resource that practitioners, researchers, and managers can rely on to provide timely information about current research developments, trends, best practices, and changes in the profession.
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Xplore Articles related to Reconnaissance
Back to TopRealization of position selection simulation evaluation system for artillery reconnaissance radar
2010 International Conference On Computer Design and Applications, 2010
Aiming at improving the position selection limitation of artillery reconnaissance radar by map work and field reconnaissance, Multigen Creator and Vega were adopted as the development platform of visual simulation software, the position selection simulation evaluation system of artillery reconnaissance radar was realized. The structure and function of system, three dimension scene modeling and terrain selection evaluation were discussed. Several ...
Decision Making for Rapid Information Acquisition in the Reconnaissance of Random Fields
Proceedings of the IEEE, 2012
In this paper, research into several aspects of robot-enabled reconnaissance of random fields is reported. The work has two major components: the underlying theory of information acquisition in the exploration of unknown fields and the results of experiments on how humans use sensor-equipped robots to perform a simulated reconnaissance exercise. The theoretical framework reported herein extends work on robotic exploration ...
Journal of Systems Engineering and Electronics, 2018
In the design problem of low earth orbit (LEO) reconnaissance satellite constellation, optimization of coverage performance is the design goal in most current methods. However, in the using process, the user only concerns with the detection capabilities rather than coverage performance. To establish the relationship between these two aspects, the reconnaissance processes of normal stochastic targets are considered and the ...
Multi-agent-based battlefield reconnaissance simulation by novel task decompositionand allocation
2010 5th International Conference on Computer Science & Education, 2010
In order to support the advanced concept technology demonstration of intelligence reconnaissance activities, multi-agent-based battlefield reconnaissance simulation is studied to provide enough detail to examine dynamic tactical process by a novel method of task decomposition and allocation. Our work includes four parts: (1) describing task by means of Behavior Definition Frame; (2) analyzing task by presenting a role-agent mapping mechanism, ...
Multi-UAV cooperative reconnaissance decision-making based on Lingo
2017 2nd Asia-Pacific Conference on Intelligent Robot Systems (ACIRS), 2017
In this paper, the decision-making problem of multi-UAVs cooperative reconnaissance under uncertainty environment is considered. Since multi-UAV cooperative reconnaissance task decision making problem is not only a complicated multi-objective optimization and decision problem with multi- constraint, but also a large-scale coordination control problem. We construct the mathematical model according to the maximization of reconnaissance gains of all task areas for ...
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Educational Resources on Reconnaissance
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IEEE-USA E-Books
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Realization of position selection simulation evaluation system for artillery reconnaissance radar
Aiming at improving the position selection limitation of artillery reconnaissance radar by map work and field reconnaissance, Multigen Creator and Vega were adopted as the development platform of visual simulation software, the position selection simulation evaluation system of artillery reconnaissance radar was realized. The structure and function of system, three dimension scene modeling and terrain selection evaluation were discussed. Several key techniques such as improved terrain building algorithm, position evaluation algorithm were given in detail. The results show that the simulation system simulates the position selection operation process of artillery reconnaissance radar livingly and can meet the requirement of real time simulation.
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Decision Making for Rapid Information Acquisition in the Reconnaissance of Random Fields
In this paper, research into several aspects of robot-enabled reconnaissance of random fields is reported. The work has two major components: the underlying theory of information acquisition in the exploration of unknown fields and the results of experiments on how humans use sensor-equipped robots to perform a simulated reconnaissance exercise. The theoretical framework reported herein extends work on robotic exploration that has been reported by ourselves and others. Several new figures of merit for evaluating exploration strategies are proposed and compared. Using concepts from differential topology and information theory, we develop the theoretical foundation of search strategies aimed at rapid discovery of topological features (locations of critical points and critical level sets) of a priori unknown differentiable fields. The theory enables study of efficient reconnaissance strategies in which the tradeoff between speed and accuracy can be understood. The proposed approach to rapid discovery of topological features has led in a natural way to the creation of parsimonious reconnaissance routines that do not rely on any prior knowledge of the environment. The design of topology-guided search protocols uses a mathematical framework that quantifies the relationship between what is discovered and what remains to be discovered. The quantification rests on an information theory inspired model whose properties allow us to treat search as a problem in optimal information acquisition. A central theme in this approach is that “conservative” and “aggressive” search strategies can be precisely defined, and search decisions regarding “exploration” versus “exploitation” choices are informed by the rate at which the information metric is changing. The paper goes on to describe a computer game that has been designed to simulate reconnaissance of unknown fields. Players carry out reconnaissance missions by choosing sequences of motion primitives from two families of control laws that enable mobile robots to either ascend/descend in gradient directions of the field or to map contours of constant field value. The strategies that emerge from the choices of motion sequences are classified in terms of the speed with which information is acquired, the fidelity with which the acquired information represents the entire field, and the extent to which all critical level sets have been approximated. The game thus records each player's performance in acquiring information about both the topology and geometry of the unknown fields that have been randomly generated.
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In the design problem of low earth orbit (LEO) reconnaissance satellite constellation, optimization of coverage performance is the design goal in most current methods. However, in the using process, the user only concerns with the detection capabilities rather than coverage performance. To establish the relationship between these two aspects, the reconnaissance processes of normal stochastic targets are considered and the mathematic models of detection processes are built. The indicators of coverage performance are used to evaluate the detection probability and expectation of detection time delay, which are important factors in reconnaissance constellation estimation viewed from military intelligence discipline. The conclusions confirmed by the final simulation will be useful in LEO reconnaissance constellation design, optimization and evaluation.
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Multi-agent-based battlefield reconnaissance simulation by novel task decompositionand allocation
In order to support the advanced concept technology demonstration of intelligence reconnaissance activities, multi-agent-based battlefield reconnaissance simulation is studied to provide enough detail to examine dynamic tactical process by a novel method of task decomposition and allocation. Our work includes four parts: (1) describing task by means of Behavior Definition Frame; (2) analyzing task by presenting a role-agent mapping mechanism, and thus setting up a mapping from a role to an agent, i.e., from battlefield reconnaissance system's real components, to entity agents; (3) decomposing task based on logistic relationships between real components in battlefield reconnaissance system organization, by using a Task Tree decomposition approach, and allocating task by using task allocation processing module; (4) proposing case study and implementing simulation. The result demonstrated in the case study proves the feasibility and efficiency of our method and model.
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Multi-UAV cooperative reconnaissance decision-making based on Lingo
In this paper, the decision-making problem of multi-UAVs cooperative reconnaissance under uncertainty environment is considered. Since multi-UAV cooperative reconnaissance task decision making problem is not only a complicated multi-objective optimization and decision problem with multi- constraint, but also a large-scale coordination control problem. We construct the mathematical model according to the maximization of reconnaissance gains of all task areas for multi-UAVs. By balancing the reconnaissance gains among the multi-task areas in order to generate a plan that is efficient for the reconnaissance mission, the Lingo software is adopted to settle this scheduling problem. The numerical result shows that we can obtain the optimal solution for the multi-UAV cooperative reconnaissance decision-making problem by Lingo software efficiently.
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Research on the model of unmanned aerial vehicle formation cooperative reconnaissance
Air-to-ground cooperative reconnaissance with UAVs is the main application aspect in UAV's operation research. This paper addresses the problem of UAV formation cooperative reconnaissance, and the models associated with it are built which contain targets search for, identification and reconnaissance time aspects; then the factors influencing formation's cooperative reconnaissance capability are discussed with an simple but illuminating instantiation according to information share mechanism and formation constitution. Investigating the models of the problem is the basic of optimizing the constitution and share mechanism.
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Mining Large Network Reconnaissance Data
This paper examines techniques for a large network infrastructure reconnaissance and dives into a real-world case study of a nation-wide passive network vulnerability assessment. The main goal of this study is to understand methods of a large network risk evaluation and conduct practical experiments using a national network. The main contribution of this paper is a non- intrusive method of a large network infrastructure reconnaissance and an application of acquired data to measure network vulnerability exposures within the analysed network. In this study our assumption is based on an estimation that actual threats come from the actively exploited vulnerabilities. Information on exploit-targeted platforms and vulnerabilities could be easily collected from a large set of malicious websites and automatically turned into signatures. We propose an automated method of building such signatures and use those to analyse the reconnaissance data set to identify ranges of vulnerable systems.
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On FDA RF localization deception under sum difference beam reconnaissance
Different from the conventional phased-array, frequency diverse array (FDA) introduces a small frequency increment across the array element, thus yielding a range-and-time-dependent beampattern. This property motivates the application of FDA in radio frequency (RF) localization deception. In this paper, the sum and difference beams algorithm is used to test the effectiveness of the proposed method in FDA reconnaissance. Both theoretical analysis and simulation results show that the sum and difference algorithm cannot achieve FDA radar reconnaissance effectively and accurately. Therefore, compared to phased-array, FDA has a better RF localization deception performance.
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Summary form only given. In this paper, a novel robot system for a jellyfish reconnaissance and removal using unmanned aerial vehicle (UAV) and unmanned surface vehicle (USV) is introduced. In recent years, overpopulated jellyfish are threatening ocean ecosystem as well as damaging to ocean-related industries such as fishery, seaside power plants, and casualties. The damage is estimated about 300M USD per year in South Korea. To resolve this problem, a jellyfish removal net towed by trawl boats and a few of devices to prevent the influx of jellyfish have been developed. However, most of these devices have the limited usage due to environmental constraints. To solve this problem using a robotic system, the jellyfish removal robot system, named JEROS (Jellyfish Elimination RObotic Swarm), has been proposed [1]. The JEROS consists of a USV and a jellyfish remover device. The USV can perform a jellyfish removal task using an autonomous navigation system. The jellyfish remover device is originally designed to shred jellyfish. It is additionally designed using a conveyor device to remove venomous jellyfish without shredding. JEROS is extended to a swarm robot system to enhance the performance of jellyfish removal [2]. The swarm robot system performs the jellyfish removal task while maintaining a formation. The UAV-type jellyfish reconnaissance system is proposed. The UAV flies over the sea along a coverage path to search a swarm of jellyfish. A camera mounted on the UAV takes images of the sea surface and a jellyfish recognition algorithm based on a deep learning finds distribution of jellyfish using the taken images. The jellyfish removal task is performed by JEROS in combination with the reconnaissance system. The reconnaissance system recognizes the distribution of jellyfish and transmits the position of the distribution to the JEROS system. The JEROS system generates a path from a starting position to the received region and follows the path. On arriving, the JEROS system remove jellyfish using the jellyfish remover device while following a coverage path.
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An Effective Address Mutation Approach for Disrupting Reconnaissance Attacks
Network reconnaissance of addresses and ports is prerequisite to a vast majority of cyber attacks. Meanwhile, the static address configuration of networks and hosts simplifies adversarial reconnaissance for target discovery. Although the randomization of host addresses has been suggested as a proactive disruption mechanism against such reconnaissance, the proposed approaches do not exploit the full potentials of address randomization in provision of unpredictability and attack adaptability. Moreover, these approaches do not provide thorough analysis on effectiveness and limitations of address randomization against relevant threat models, including stealthy scanning and worms. In this paper, we present an effective address randomization technique, called random host address mutation (RHM), that turns end-hosts into untraceable moving targets. This technique achieves maximum efficacy by allowing address randomization to be highly unpredictable and fast, and adaptive to adversarial behavior, while incurring low operational and reconfiguration overhead. Our approach achieves the following objectives: (1) it achieves high uncertainty in adversary scanning by modeling address mutation randomization as a multi-level satisfiability problem; (2) it adapts the mutation scheme by fast characterization of adversarial reconnaissance patterns; (3) it achieves high mutation rate by separating mutation from end- hosts and managing it via network appliances; and (4) it preserves network integrity, manageability and performance by bounding the size of routing tables, preserving end-to-end reachability, and efficient handling of reconfiguration updates. Our extensive analyses and simulation show that the RHM distorts adversarial reconnaissance, slows down (deters) the attack, and increases its detectability. Consequently, the RHM is effective in countering a significant number of sophisticated threat models, including reconnaissance, stealthy/evasive scanning methods, and targeted attacks. We also address limitations of our approach in terms of effectiveness and applicability.
Jobs related to Reconnaissance
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RF Signals and Systems Engineer - Washington, D.C. - SEAL
Georgia Tech Research Institute (GTRI)
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High Performance Computational Algorithm Developer - SEAL
Georgia Tech Research Institute (GTRI)
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Model-Based Systems Engineer (I/II) - SEAL
Georgia Tech Research Institute (GTRI)
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Algorithm Developer - SEAL
Georgia Tech Research Institute (GTRI)
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Algorithm Developer - SEAL
Georgia Tech Research Institute (GTRI)
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Algorithm Engineer – Machine Learning - SEAL
Georgia Tech Research Institute (GTRI)
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Technical Project Manager - Washington, D.C. - SEAL
Georgia Tech Research Institute (GTRI)
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Algorithm Developer - SEAL
Georgia Tech Research Institute (GTRI)
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Optical Scientist/Engineer I/II - EOSL
Georgia Tech Research Institute (GTRI)
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EO/IR Algorithm & Software Engineer - EOSL
Georgia Tech Research Institute (GTRI)
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Optical Scientist/Engineer, Sr - EOSL
Georgia Tech Research Institute (GTRI)
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Optical Systems Engineer - EOSL
Georgia Tech Research Institute (GTRI)