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conference on Advanced Signal Processing algorithms, architectures, and Implementations IX

作者： Izzetoglu, M Akgül, T Drexel Univ Dept Elect & Comp Engn Philadelphia PA 19104 USA

ISBN: (纸本)0819432938

In this paper we introduce a. multi-scale deconvolution technique performed in the scale-domain. In sensor array applications such as in radar, sonar and seismic processing, the sensor outputs are modeled as the convolution of the unknown source signal with various unknown system impulse responses that are scaled versions of each other with unknown scale parameters. In many applications these signals or the scaling parameters are needed to be estimated only from the sensor outputs. In our earlier work, we estimated the unknown scale parameters by using properties of the scale transform and then employed existing deconvolution algorithms. Here, we derive the multiscale blind deconvolution algorithm in the scale transform domain. The performance of the method is illustrated using simulation examples.

关键词： sensors Deconvolution Reflectors Convolution Signal processing Algorithm development Computer simulations Electronic filtering Image processing Radar

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Multi-level data fusion approach for gradually upgrading the performances of identity verification systems

Multi-level data fusion approach for gradually upgrading the...

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

作者： Verlinde, Patrick Druyts, Pascal Chollet, Gerard Acheroy, Marc Royal Military Acad/Signal and Image Cent Brussels Belgium

The aim of this paper is to propose a strategy that uses data fusion at three different levels to gradually improve the performance of an identity verification system. In a first step temporal data fusion can be used to combine multiple instances of a single (mono-modal) expert to reduce its measurement variance. If system performance after this first step is not good enough to satisfy the end-user's needs, one can improve it by fusing in a second step results of multiple experts working on the same (biometric) modality. For this approach to work, it is supposed that the respective classification errors of the different experts are (at least partially) de-correlated. Finally, if the verification system's performance after this second step is still not good enough, one will be forced to move on to the third step in which performance can be improved by using multiple experts working on different (biometric) modalities. To be useful however, these experts have to be chosen in such a way that adding the extra modalities increases the separation in the multi-dimensional modality-space between the distributions of the different populations that have to be classified by the system. This kind of level-based strategy allows to gradually tune the performance of an identity verification system to the end-user's requirements while controlling the increase of investment costs. In this paper results of several fusion modules will be shown at each level. All experiments have been performed on the same multi-modal database to be able to compare the gain in performance each time one goes up a level.

关键词： sensor data fusion

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Multi-level data fusion approach for gradually upgrading the performances of identity verification systems

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 14-25页

作者： Verlinde, Patrick Druyts, Pascal Chollet, Gerard Acheroy, Marc Royal Military Acad/Signal and Image Cent Brussels Belgium

关键词： sensor data fusion

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Temporal fusion a basic for neural plasticity in the visual pathways

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 79-90页

作者： Navabi, Homayoun Tehran Iran

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： Neural networks

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Experiments in the control of perception in a multi-sensor system

Experiments in the control of perception in a multi-sensor s...

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Proceedings of the 1999 IEEE/SICE/RSJ International conference on Multisensor fusion and Integration for Intelligent Systems, MFI'99

作者： Celinski, Tomasz McCarragher, Brenan Australian Natl Univ Canberra

The paper presents a new approach to management of multiple sensors and perception algorithms in a multi-sensor robotic system. The approach involves real-time selection of process monitors by a sensory Perception Controller. The selection is based on the minimization of the expected cost of perception with constraints on the uncertainty of perception. The effectiveness and usefulness of the approach is evaluated through experiments involving a range of sensing modalities which may typically be encountered in robotic applications.

关键词： sensor data fusion

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COBRA based infrastructure (CORBIS) for sensor data fusion systems

COBRA based infrastructure (CORBIS) for sensor data fusion s...

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

作者： Balci, Metin Kuru, Selahattin Software Development Cent Kocaeli Turkey

The Common Object Request Broker Architecture (COBRA) has been proven to be effective for application in the Data fusion domain. However, the benefits of this system have not yet been fully realized because of unresolved issues concerning reliability, fault-tolerance and real-time/fast enough QoS behavior of the system. In view of this, an attempt has been made to develop a domain specific environment with the commercially available standard products. The result is a COBRA based infrastructure (CORBIS) that provide interfaces and mechanisms for various applications and services.

关键词： Computer software

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Review of high-level multisensor fusion: Approaches and applications

Review of high-level multisensor fusion: Approaches and appl...

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Proceedings of the 1999 IEEE/SICE/RSJ International conference on Multisensor fusion and Integration for Intelligent Systems, MFI'99

作者： Luo, Ren C. Su, Kuo L. Natl Chung Cheng Univ Chia-Yi Taiwan

The need for intelligent systems that can be important in the future trends. It is impossibly arrived at the goal, but be combined with multi sensor fusion. The potential advantages in multisensor fusion can be obtained more accurately, concerning feature that are impossible to perceive with individual sensors, as well as in less time, and at a lesser cost. The characterization most commonly encountered in the rapidly growing multisensor fusion literature based on level of detail in the information is that of the now well known triple low level (data level), medium level (feature level) and high level (decision level). The development of high-level multisensor fusion representations is very important, in order to construct advanced intelligent systems. The paper begins with review on the fundamental principles about high-level multisensor fusion, and has been employed in some applications in the object. Finally, we compare with the decision algorithms each other in the high-level multisensor fusion.

关键词： sensor data fusion

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sensor fusion options for ballistic missile defense interceptor applications

Sensor fusion options for ballistic missile defense intercep...

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

作者： Bjork, Charles Morris, Norman Dasarathy, Belur V. Smith, Bart Allen, Doug Prestwood, William T. Nichols Research Corp Huntsville AL United States

Critical elements of future exoatmospheric interceptor systems are intelligent processing (IP) techniques which can effectively combine sensor data from disparate sensors. This paper summarizes the impact on discrimination performance of several feature and classifier fusion techniques, which can be used as part of the overall IP approach. These techniques are implemented either within the Fused sensor Discrimination (FuSeD) Testbed, or off-line as building blocks that can be modified to assess differing fusion approaches, classifiers and their impact on interceptor requirements. Several optional approaches for combining the data at the different levels, i.e, feature and classifier levels, are discussed in this paper and a comparison of performance results is shown. Approaches yielding promising results must still operate within the timeline and memory constraints on board the interceptor. A hybrid fusion approach is implemented at the feature level through the use of feature sets input to specific classifiers (currently two classifiers are employed). The output of the fusion process contains an estimate of the confidence in the data and the discrimination decisions. The confidence in the data and decisions can be used in real time to dynamically select different sensor feature data, classifiers, or to request additional sensor data on specific objects that have not been confidently identified as 'lethal' or 'non-lethal'. However, dynamic selection requires an understanding of the impact of various combinations of feature sets and classifier options. Accordingly, the paper presents the various tools for exploring these options and illustrates their usage with data sets generated to realistically simulate the world of Ballistic Missile Defense (BMD) interceptor applications.

关键词： sensor data fusion

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Reconfigurable sensor fusion processing hardware

Reconfigurable sensor fusion processing hardware

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Proceedings of the 1999 Artificial Neural Networks in Engineering conference (ANNIE '99)

作者： Stoica, Adrian Thomas, Tyson J. Li, Wei-Te Weldon, David A. Duong, Tuan A. Daud, Taher California Inst of Technology Pasadena United States

Smart sensing as required by a variety of space, defense and civilian applications demands a more flexible, adaptive processing at the sensor level to increase functionality and the quality of the sensor information. Computational intelligence techniques (neural, fuzzy and evolutionary) play an important role in pre-processing of the sensor data and in sensor fusion. Most applications using computational intelligence techniques rely on software solutions;however, smart sensors would most importantly benefit from hardware implementations (compact, low power, system-on-a-chip). The focus of this paper is on a set of reconfigurable ASICs, developed to implement or benefit from computational intelligence techniques. A first set of chips is targeted toward seamlessly combining rule-based, fuzzy logic, and neural network techniques to achieve parallel fusion of sensor data in compact low power VLSI. A second set of chips attempts at automatic on-chip synthesis of computational electronic circuits under the control of evolutionary algorithms. Several prototype analog VLSI chips have been fabricated and tested.

关键词： Neural networks

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

Study of a modified Dempster-Shafer approach using an expect...

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

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