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检索条件"任意字段=Multisensor. Multisource Information Fusion: Architectures, Algorithms, and Applications 2003"

共 284 条记录，以下是221-230 订阅

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SAWA: An assistant for higher-level fusion and situation awareness

SAWA: An assistant for higher-level fusion and situation awa...

引用

Conference on multisensor. multisource information fusion

作者： Matheus, CJ Kokar, MM Baclawski, K Letkowski, JA Call, C Hinman, M Salerno, J Boulware, D Versatile Informat Syst Inc Framingham MA 01701 USA

ISBN: (纸本)0819457981

Situation awareness involves the identification and monitoring of relationships among level-one objects. This problem in general is intractable (i.e., there is a potentially infinite number of relations that could be tracked) and thus requires additional constraints and guidance defined by the user if there is to be any hope of creating practical situation awareness systems. This paper describes a Situation Awareness Assistant (SAWA) that facilitates the development of user-defined domain knowledge in the form of formal ontologies and rule sets and then permits the application of the domain knowledge to the monitoring of relevant relations as they occur in evolving situations. SAWA includes tools for developing ontologies in OWL and rules in SWRL and provides runtime components for collecting event data, storing and querying the data, monitoring relevant relations and viewing the results through a graphical user interface. An application of SAWA to a scenario from the domain of supply logistics is also presented.

关键词： situation awareness level-two fusion ontologies formal reasoning OWL SWRL

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A generic model of tactical plan recognition for threat assessment

A generic model of tactical plan recognition for threat asse...

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Conference on multisensor. multisource information fusion

作者： Suzic, R Swedish Def Res Agcy FOI SE-17290 Stockholm Sweden

ISBN: (纸本)0819457981

Plan recognition has to be performed in a statistically robust manner concerning a possibly infinite number of tactical situations and different types of units. We need a generic model for tactical plan recognition where we combine observations and a priori knowledge in a flexible manner by using suitable methodologies and by having a large hypothesis space taken into account. Threat and therefore observed agent's plans should be put into a context. Here, we propose Multi-Entity Bayesian Networks (MEBN), introduced in [2], which enable the composition of Bayesian Networks from the network pieces, as the key methodology when designing flexible plan recognition models. However, Bayesian network pieces (fragments) must be compatible and therefore we propose ontology for generic plan recognition using Bayesian network fragments. Additionally, we claim that by using multi-entity network fragments we expand the hypothesis space and using this approach various multi-agents structures can be expressed. Our final contribution is that we incorporate the use of explicit utilities in our plan recognition model.

关键词： Fuzzy logic Sensors Network architectures Data modeling Defense and security Defense technologies Environmental sensing Stochastic processes information fusion Statistical modeling

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Image fusion with the hybrid evolutionary algorithm and response analysis

Image fusion with the hybrid evolutionary algorithm and resp...

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Conference on multisensor. multisource information fusion

作者： Maslov, IV CUNY Dept Comp Sci Grad Ctr New York NY 10016 USA

ISBN: (纸本)0819457981

information fusion is a rapidly developing research area aimed at creating methods and tools capable of augmenting security and defense systems with the state-of-the-art computational power and intelligence. An important part of information fusion, image fusion serves as the basis for a fully automatic object and target recognition. Image fusion maps images of the same scene received from different sensors into a common reference system. Using sensors of different types gives rise to a problem of finding a set of invariant features that help overrun the imagery difference caused by the different types of sensors. The paper describes an image fusion method based on the combination of the hybrid evolutionary algorithm and image local response. The latter is defined as an image transform R(V) that maps an image into itself after a geometric transformation A(V) defined by a parameter vector V is applied to the image. The transform R(V) identifies the dynamic content of the image, i.e. the salient features that are most responsive to the geometric transformation A(V). Moreover, since R(V) maps the image into itself, the result of the mapping is largely invariant to the type of the sensor used to obtain the image. Image fusion is stated as the global optimization problem of finding a proper transformation A(V) that minimizes the difference between the images subject to fusion. Hybrid evolutionary algorithm can be applied to solving the problem. Since the search for the optimal parameter vector V is conducted in the response space rather than in the actual image space, the differences in the sensor types can be significantly alleviated.

关键词： information fusion image fusion target recognition optimization hybrid evolutionary algorithm response analysis

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Real time implementation of image alignment and fusion

Real time implementation of image alignment and fusion

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Conference on multisensor. multisource information fusion

作者： Dwyer, D Smith, M Dale, J Heather, J Octec Ltd Western Ctr Bracknell RG12 1RW Berks England

ISBN: (纸本)0819457981

Many modern imaging and surveillance systems contain more than one sensor. For example, most modern airborne imaging pods contain at least visible and infrared sensors. Often these systems have a single display that is only capable of showing data from either camera, and thereby fail to exploit the benefit of having simultaneous multi-spectral data available to the user. It can be advantageous to capture all spectral features within each image and to display a fused result rather than single band imagery. This paper discusses the key processes necessary for an image fusion system and then describes how they were implemented in a real-time, rugged hardware system. The problems of temporal and spatial misalignment of the sensors and the process of electronic image warping must be solved before the image data is fused. The techniques used to align the two inputs to the fusion system are described and a summary is given of our research into automatic alignment techniques. The benefits of different image fusion schemes are discussed and those that were implemented are described. The paper concludes with a summary of the real-time implementation of image alignment and image fusion by Octec and Waterfall Solutions and the problems that have been encountered and overcome.

关键词： image alignment image fusion real time image processing

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Multiple objective optimization for active sensor management

Multiple objective optimization for active sensor management

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Conference on multisensor. multisource information fusion

作者： Page, SF Dolia, AN Harris, CJ White, NM Univ Southampton Sch Elect & Comp Sci Southampton SO9 5NH Hants England

ISBN: (纸本)0819457981

The performance of a multi-sensor data fusion system is inherently constrained by the configuration of the given sensor suite. Intelligent or adaptive control of sensor resources has been shown to offer improved fusion performance in many applications. Common approaches to sensor management select sensor observation tasks that are optimal in terms of a measure of information. However, optimising for information alone is inherently sub-optimal as it does not take account of any other system requirements such as stealth or sensor power conservation. We discuss the issues relating to developing a suite of performance metrics for optimising multi-sensor systems and propose some candidate metrics. In addition it may not always be necessary to maximize information gain, in some cases small increases in information gain may take place at the cost of large sensor resource requirements. Additionally, the problems of sensor tasking and placement are usually treated separately, leading to a lack of coherency between sensor management frameworks. We propose a novel approach based on a high level decentralized information-theoretic sensor management architecture that unifies the processes of sensor tasking and sensor placement into a single framework. Sensors are controlled using a minimax multiple objective optimisation approach in order to address probability of target detection, sensor power consumption, and sensor survivability whilst maintaining a target estimation covariance threshold. We demonstrate the potential of the approach through simulation of a multi-sensor, target tracking scenario and compare the results with a single objective information based approach.

关键词： sensor management resource allocation information filter multi-objective optimization target tracking

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Sensor fusion for coastal waters surveillance

Sensor fusion for coastal waters surveillance

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Conference on multisensor. multisource information fusion

作者： Doshi, B Benmohamed, L Chimento, P Wang, IJ Johns Hopkins Univ Appl Phys Lab Laurel MD 20723 USA

ISBN: (纸本)0819457981

We describe a large sensor field whose mission is to protect coastal waters by detecting objects like submarines. The system is buoy-based and distributed over a littoral area. The opportunities for detection are short and intermittent and the signal to noise ratio is low. The topology of the field changes with time due to currents, wind, tides and storms. The field has a number of gateway nodes that have the capability to transmit off-field through a satellite, a ship or a plane. We propose an approach to fusion that includes on-buoy processing, cooperative processing with nearest neighbors and the potential for off-field processing. Each stage of processing tries both to minimize false positive events and to maximize the probability of detection when an object is present. It also tries to minimize power used in order to prolong the life of the field. We analyze the optimal placement of gateway nodes in the field to minimize power consumption and maximize reliability and probability of successful off-field transmission. We analyze the duty cycles of the sensor and gateway nodes to optimize lifetime. We also analyze the traffic that the field will be expected to handle in order to support network control and coordination, distributed fusion, off-field communication (including queries and responses, and reporting of detection events), forwarding of traffic through individual sensor nodes toward gateways or for fusion.

关键词： distributed sensor field sensor networks coastal surveillance

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Hybrid framework for fusion 2+in multi-multi air engagement

Hybrid framework for fusion 2+in multi-multi air engagement

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Conference on multisensor. multisource information fusion

作者： Lee, KD Llinas, J Adleson, R Decis Analyt Corp Arlington VA 22202 USA

ISBN: (纸本)0819457981

fusion 2+ of air-to-air engagement involves pressing, real-time constraints and very large amounts of imperfect data. Real-time data acquired during an air-to-air engagement will have different types of imperfection;two representative classes of imperfection are vagueness and ambiguity in the data. However, the current approaches of managing fusion 2+ are limited to utilize either vague data or ambiguous data. The most popular fusion technique for vague data is Fuzzy Logic, and for ambiguous data, the Bayesian Network. The challenge addressed in this proposal is to explore the framework of a hybrid processing fusion 2+ model that can formally process both vague (fuzzy) and ambiguous (probabilistic) data types. There are two major issues for building this fusion 2+ model. The first issue is to mathematically integrate the heterogeneous models, which have different domains, probability and possibility. The second issue is to programmatically integrate two different S/Ws. For solving the first issue, this research explores and adopts two novel transformation methods between probability and possibility and compares the sensitivity between methods. Also this research provides an Object Oriented Tool for building a hybrid model by adopting an Application Programming Interface, so that we can model the complex (multi-to-multi) fusion 2+ model of an air-to-air engagement.

关键词： fusion 2+ situation awareness Bayesian networks fuzzy logic Application Programming Interface (API)

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MASM: A market architecture for sensor management in distributed sensor networks

MASM: A market architecture for sensor management in distrib...

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Conference on multisensor. multisource information fusion

作者： Viswanath, A Mullen, T Hall, D Garga, A Penn State Univ Sch Informat Sci & Technol University Pk PA 16802 USA

ISBN: (纸本)0819457981

Rapid developments in sensor technology and its applications have energized research efforts towards devising a firm theoretical foundation for sensor management. Ubiquitous sensing, wide bandwidth communications and distributed processing provide both opportunities and challenges for sensor and process control and optimization. Traditional optimization techniques do not have the ability to simultaneously consider the wildly non-commensurate measures involved in sensor management in a single optimization routine. Market-oriented programming provides a valuable and principled paradigm to designing systems to solve this dynamic and distributed resource allocation problem. We have modeled the sensor management scenario as a competitive market, wherein the sensor manager holds a combinatorial auction to sell the various items produced by the sensors and the communication channels. However, standard auction mechanisms have been found not to be directly applicable to the sensor management domain. For this purpose, we have developed a specialized market architecture MASM (Market architecture for Sensor Management). In MASM, the mission manager is responsible for deciding task allocations to the consumers and their corresponding budgets and the sensor manager is responsible for resource allocation to the various consumers. In addition to having a modified combinatorial winner determination algorithm, MASM has specialized sensor network modules that address commensurability issues between consumers and producers in the sensor network domain. A preliminary multi-sensor, multi-target simulation environment has been implemented to test the performance of the proposed system. MASM outperformed the information theoretic sensor manager in meeting the mission objectives in the simulation experiments.

关键词： sensor management market-oriented programming combinatorial auctions genetic algorithms information theory

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A group tracking algorithm for ground vehicle convoys

A group tracking algorithm for ground vehicle convoys

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Conference on multisensor. multisource information fusion

作者： Chin, WC Lee, HB Xiao, XH Ng, GW How, KY DSO Natl Labs Singapore 118230 Singapore

ISBN: (纸本)0819457981

Tracking multiple ground targets under clutter and in real time poses several likely challenges: vehicles often get masked by foliage or line-of-sight (LOS) problems, manifesting in misdetections and false alarms. Further complications also arise when groups of vehicles merge or split. This paper presents an attempt to address these issues using a group tracking approach. Group tracking is a way to ameliorate, or at least soften the impact of such issues from the hope that at least partial information will be received from each target group even when the probability of detection, P-D of each individual member is low. A Strongest Neighbour Association (SNA) method of measurement-to-track association based on space-time reasoning and track-measurement similarity measures has been derived. We combine the association strengths of the space-time dynamics, the degree-of-overlap and the historical affinity metrics to relate measurements and tracks. The state estimation is based on standard Kalman filter. Lastly, a Pairwise Historical Affinity Ratios (PHAR) is proposed for the detection of a split scenario. This method has been tested to work well on a simulated convoy-splitting scenario. Monte Carlo experiment runs of six different error rates with five different compositions of errors have been conducted to assess the performance of the tracker. Results indicated that the group tracker remains robust (> 80% precision) even in the presence of high individual source track error rates of up to 30%.

关键词： group tracking strongest neighbour association Kalman filtering data fusion

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Prior knowledge integration of road dependant ground target behaviour for improving tracking reliability

Prior knowledge integration of road dependant ground target ...

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Conference on multisensor. multisource information fusion

作者： Gattein, S Vannoorenberghe, P Contat, M EADS S&DE Voie Future F-27106 Val De Reuil France

ISBN: (纸本)0819457981

This paper describes an algorithm for tracking ground targets, mainly based on measurements from a MTI radar. We examine the use of prior knowledge on target type for automatically improving the performance of a purely kinematic tracker. This tracker is an adaptation from a Variable Structure Interacting Multiple Model (VS-IMM) estimator acting within an S-Dimensional Assignment method. The algorithm can thus track several targets with false alarms, and the variable structure allows to use only the relevant dynamic models relative to roads in the vicinity of the target's prediction. However the sets of possible on-road and off-road models do not interact as in the usual IMM mechanism. Instead the on-road behaviour of a target across S-I radar scans is optimally managed in a hypothesis tree, since we do not mix incompatible road models. However, both global on-road and off-road behaviours are handled by mode transition probabilities, making it possible to track targets that change their behaviour regarding the road network with the same algorithm. Next an automatic measured type data integration scheme is examined, that can be connected to the above kinematic framework. The incoming measured type data is modelled by a belief function to reflect uncertainty, as well as the sensor's reliability. Simulation results show the operation of the kinematic tracker for road targets, illustrating the relevance of the variable structure dynamic model set.

关键词： data fusion target tracking VS-MM S-D assignment belief function

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