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Proceedings of the 1999 sensor fusion: architectures, algorithms, and applications III

作者： Li, Lingjie Luo, Zhi-Quan Wong, K.Max Bosse, Eloi McMaster Univ Hamilton Ont Canada

We consider the problem of identify fusion for a multi-sensor target tracking system whereby sensors generate reports on the target identities. Since the sensor reports are typically fuzzy, 'incomplete' and inconsistent, the fusion of such sensor reports becomes a major challenge. In this paper, we introduce a new identify fusion approach based on the minimization of inconsistencies between the sensor reports by using a convex Quadratic Programming (QP) and linear programming (LP) formulation. In contrast to the Dempster-Shafer's evidential reasoning approach which suffers from exponentially growing complexity, our approach is highly efficient (polynomial time solvable). Moreover, our approach is capable of fusing 'Ratio type' sensor reports, thus it is more general than the evidential reasoning theory. When the sensor reports are consistent, the solution generated by the new fusion method can be shown to converge to the true probability distribution. Simulation work shows that our method generates reasonable fusion results, and when only 'Subset type' sensor reports are present, it produces fusion results similar to that obtained via the evidential reasoning theory.

关键词： sensor data fusion

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Fuzzy multisensor tracking system

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 279-287页

作者： Chan, Keith C.C. Lee, Vika Leung, Henry Hong Kong Polytechnic Univ Kowloon Hong Kong

Many multi-sensor target tracking systems are developed under the assumptions that data association is too complex and computational requirement is too excessive for centralized fusion approaches to be practical. In addition, it is also assumed that the noise component is relatively small, that there are no missed detection and that the scanning interval is relatively short, etc. Many multi-sensor tracking systems have been shown to be able to perform effectively when tested with simulated data generated under these assumptions. However, careful investigation into the characteristics of several sets of real data reveals that these assumptions cannot always be made validly. In this paper, we first describe the characteristics of a real multisensor tracking environment and explain why existing systems may not be able to perform their task effectively in such environment. We then present a data fusion technique that can overcome some of the weaknesses of these systems. This technique consists of three steps: (i) estimation of synchronization error using an adaptive learning approach; (ii) adjustment of measured positions of a target in case of missed detection; and (iii) prediction of the next target position using a fuzzy logic based algorithm. For performance evaluation, we tested the technique using different sets of real and simulated data. The results obtained are very satisfactory.

关键词： sensor data fusion

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Neuro-dynamic programming for adaptive fusion complexity control

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 398-409页

作者： Ross, Kenneth N. Chaney, Ronald D. ALPHATECH Inc Burlington United States

The prodigious amount of information provided by surveillance systems and other information sources has created unprecedented opportunities for achieving situation awareness. Because the mission's and user's needs are constantly evolving, fusion control strategies must adapt to these changing requirements. However, the optimal control problem with the desired adaptive control capabilities is enormously complex. Therefore, we solve the adaptive fusion control problem approximately using a methodology called Neuro-Dynamic Programming (NDP) that combines elements of dynamic programming, simulation-based reinforcement learning, and statistical inference techniques. This work demonstrates the promise of using NDP for adaptive fusion control by using it to allocate computational resources to Bayesian belief networks that use a variety of data types (e.g., SAR, MTI, ELINT, and terrain databases) to track and identify clusters of vehicles. We have significantly extended previous work by using NDP to adapt the fusion process itself in addition to deciding which clusters should get their inference updated. fusion within the Bayesian networks was adapted by using NDP to select the subset of available data to be used when updating the inference. We also extended previous work by using a dynamic scenario with moving vehicles for training and testing models.

关键词： sensor data fusion

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General software design for multisensor data fusion

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 230-239页

作者： Junliang, Zhang Yuming, Zhao 54th Research Inst of Electronic Industry Shijiazhuang China

In this paper a general method of software design for multisensor data fusion is discussed in detail, which adopts object-oriented technology under UNIX operation system. The software for multisensor data fusion is divided into six functional modules: data collection, database management, GIS, target display and alarming data simulation etc. Furthermore, the primary function, the components and some realization methods of each modular is given. The interfaces among these functional modular relations are discussed. The data exchange among each functional modular is performed by interprocess communication IPC, including message queue, semaphore and shared memory. Thus, each functional modular is executed independently, which reduces the dependence among functional modules and helps software programming and testing. This software for multisensor data fusion is designed as hierarchical structure by the inheritance character of classes. Each functional modular is abstracted and encapsulated through class structure, which avoids software redundancy and enhances readability.

关键词： Computer software

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Study of a modified Dempster-Shafer approach using an expected utility interval decision rule

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 34-42页

作者： Cheaito, Ali Lecours, Michel Bosse, Eloi Universite Laval Canada

The Combination operation of the conventional Dempster-Shafer algorithm has a tendency to increase exponentially the number of propositions involved in bodies of evidence by creating new ones. The aim of this paper is to explore a 'modified Dempster-Shafer' approach of fusing identity declarations emanating from different sources which include a number of radars, IFF and ESM systems in order to limit the explosion of the number of propositions. We use a non-ad hoc decision rule based on the expected utility interval (EUI) to select the most probable object in a comprehensive Platform Data Base (PDB) containing all the possible identity values that a potential target may take. We study the effect of the redistribution of the confidence levels of the eliminated propositions which otherwise overload the real-time data fusion system; these eliminated confidence levels can in particular be assigned to ignorance, or uniformly added to the remaining propositions and the ignorance. A scenario has been selected to demonstrate the performance of our modified Dempster-Shafer method of evidential reasoning.

关键词： sensor data fusion

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Development of emergent processing loops as a system of systems concept

Development of emergent processing loops as a system of syst...

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conference on sensor fusion - architectures, algorithms, and applications III

作者： Gainey, J Blasch, E USAF Res Lab Sensors Directorate Wright Patterson AFB OH 45433 USA

ISBN: (纸本)0819431931

This paper describes an engineering approach toward implementing the current neuroscientific understanding of how the primate brain fuses, or integrates, "'information" in the decision-making process. We describe a System of Systems (SoS) design far improving the overall performance, capabilities, operational robustness, and user confidence in Identification (ID) systems and show how it could be applied to biometrics security. We use the physio-associative temporal sensor integration algorithm (PATSIA) which is motivated by observed functions and interactions of the thalamus, hippocampus, and cortical structures in the brain. PATSIA utilizes signal theory mathematics to model how the human efficiently perceives and uses information from the environment. The hybrid architecture implements a possible SoS-level description of the Joint Directors of US Laboratories (JDL) for fusion Working Group's functional description involving 5 levels of fusion (i.e., Preprocessing, kinematic, situation, threat, and process refinement) and their associated definitions. This SoS architecture proposes dynamic sensor and knowledge-source integration by implementing multiple Emergent Processing Loops (EPL) for Predicting, feature Extracting, Matching, and Searching both static and dynamic databases like MSTAR's PEMS loops. Biologically, this effort demonstrates these objectives by modeling similar processes from the eyes, ears. and somatosensory channels, through the thalamus, and to the cortices as appropriate while using the hippocampus for short-term memory search and storage as necessary. The particular approach demonstrated incorporates commercially available speaker verification (simulating 1D audio/signal inputs) and face recognition (simulating 2D video/image inputs) software and hardware to collect data and extract features to the PATSIA. The PATSIA maximizes the confidence levels for target identification or verification in dynamic situations using a belief filter. The proof o

关键词： sensor data fusion

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Bio-fusion for intelligent system control

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 410-417页

作者： Norseen, John D. Kropotov, Juri D. Kremen, Inna Z. Lockheed Martin Aeronautical Co

We present a realistic neural network - the canonical cortical module - built on basic principles of cortical organization. These principles are: opponent cells principle, assembly principle, canonical cortical circuit principle and modular principle. When applied to visual images, the network explains orientational and spatial frequency filtering functions of neurons in the striate cortex. Two patterns of joint distribution of opponent cells in the inhibitory cortical layer are presented: pinwheel and circular. These two patterns provide two Gestalt descriptions of local (within the frames of one module) visual image: circle-ness and cross-ness. These modules were shown to have a power for shape detection and texture discrimination. They also provide an enhancement of signal-to-noise ratio of input images. Being modality independent, the canonical cortical module seems to be good tool for bio-fusion for intelligent system control.

关键词： Neural networks

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Fuzzy multisensor tracking system

Fuzzy multisensor tracking system

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Proceedings of the 1999 sensor fusion: architectures, algorithms, and applications III

作者： Chan, Keith C.C. Lee, Vika Leung, Henry Hong Kong Polytechnic Univ Kowloon Hong Kong

Many multi-sensor target tracking systems are developed under the assumptions that data association is too complex and computational requirement is too excessive for centralized fusion approaches to be practical. In addition, it is also assumed that the noise component is relatively small, that there are no missed detection and that the scanning interval is relatively short, etc. Many multi-sensor tracking systems have been shown to be able to perform effectively when tested with simulated data generated under these assumptions. However, careful investigation into the characteristics of several sets of real data reveals that these assumptions cannot always be made validly. In this paper, we first describe the characteristics of a real multisensor tracking environment and explain why existing systems may not be able to perform their task effectively in such environment. We then present a data fusion technique that can overcome some of the weaknesses of these systems. This technique consists of three steps: (i) estimation of synchronization error using an adaptive learning approach;(ii) adjustment of measured positions of a target in case of missed detection;and (iii) prediction of the next target position using a fuzzy logic based algorithm. For performance evaluation, we tested the technique using different sets of real and simulated data. The results obtained are very satisfactory.

关键词： sensor data fusion

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Multi-spectral image fusion for visual display

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 359-368页

作者： Peli, Tamar Peli, Eli Ellis, Ken Stahl, Robert Atlantic Aerospace Electronics Corp Waltham United States

This paper describes a contrast-based monochromatic fusion process. The fusion process is aimed for on board real time application and it is based on practical and computationally efficient image processing components. The process maximizes the information content in the combined image, while retaining visual clues that are essential for navigation/piloting tasks. The method is a multi scale fusion process that provides a combination of pixel selection from a single image and a weighing of the two/multiple images. The spectral region is divided into spatial sub bands of different scales and orientations, and within each scale a combination rule for the corresponding pixels taken from the two components is applied. Even when the combination rule is a binary selection the combined fused image may have a combination of pixel values taken from the two components at various scales since it is taken at each scale. The visual band input is given preference in low scale, large features fusion. This fusion process provides a fused image better tuned to the natural and intuitive human perception. This is necessary for pilotage and navigation under stressful conditions, while maintaining or enhancing the targeting detection and recognition performance of proven display fusion methodologies. The fusion concept was demonstrated against imagery from image intensifiers and forward looking infrared sensors currently used by the U.S. Navy for navigation and targeting. The approach is easily extendible to more than two bands.

关键词： Image processing

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Temporal fusion a basic for neural plasticity in the visual pathways

Temporal fusion a basic for neural plasticity in the visual ...

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conference on sensor fusion - architectures, algorithms, and applications III

作者： Navabi, H IPM Inst Studies Thoret Phys & Math ISRF Tehran Iran

ISBN: (纸本)0819431931

Vision is an excellent example of the rich interplay between computational and biological approaches to the understanding of complex information processing tasks. Studies of biological solutions to the computational problems of vision, such as contrast masking, movement detection, orientation selectivity has created many controversies in visual neuroscience. Recent neurobiological findings suggest an experimental paradigm that gives emphasis to strategies, which rely on the combined activities of cells or cell assembly for information transforms. This new perspective explains an integrated synaptic facilitation that is contingent upon the emergent spatial and temporal properties of cell activities. The paper briefly presents a novel biologically inspired adaptive architecture that can serve for analysis of cell response dynamics to encode analog (gray scale) visual sensory data under varying conditions. The key will be the active representation of visual objects temporal characteristics, i.e., the exposures (or presentation) time and the syntactic structure to achieve invariance for the fundamental problems of scene segmentation and figure-ground separation. The basic neural mechanism is that of plastic relationship between and within participating cells or cellular groups with known receptive field organizations. Our system behavior is tested with numerous parametric psychophysical data, and the selected simulation samples predict: Only the active integration (or fusion) from multiple exposure to the sequence of sensory visual information can yield a reliable encode to extract salient features of visual objects, in partially unknown and possibly changing environments.

关键词： cell assembly active representation plasticity figure_ground separation receptive field organization

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