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Conference on sensor fusion - architectures, algorithms, and applications iii

作者： Malhotra, RP Yufik, YM USAF Res Lab Sensors Directorate Wright Patterson AFB OH 45433 USA

ISBN: (纸本)0819431931

We discuss Virtual Associative Networks (VANs) emd their relevance for addressing computationally prohibitive sensor fusion problems (with results in Dynamic sensor Management). To our knowledge, this discussion of VAN technology for sensor fusion is unique and our current result involving VANs for Dynamic sensor Management is the first of its kind. The following provides methodology, results, and extensions.

关键词： neurocomputation cognitive science sensor fusion sensor Management neural networks

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Partially decentralized architecture for fusing active (radar) and passive (infrared) measurement data

Partially decentralized architecture for fusing active (rada...

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proceedings of the 1999 sensor fusion: architectures, algorithms, and applications iii

作者： van Huyssteen, David Farooq, Mohamad Ottawa Ont Canada

A decentralized technique in which kinematic information from a radar and infrared imager are fused has been developed. To validate its effectiveness, the technique has been compared to a sequentially based Kalman filter via Monte Carlo simulation. The comparison showed that the decentralized technique is a potentially viable alternative.

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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sensor fusion cognition using belief filtering for tracking and identification

Sensor fusion cognition using belief filtering for tracking ...

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Conference on sensor fusion - architectures, algorithms, and applications iii

作者： Blasch, E Hong, L SNAT AFRL Wright Patterson AFB OH 45433 USA

ISBN: (纸本)0819431931

Humans exhibit remarkable abilities to estimate, filter, predict, and fuse information in target tracking tasks. To improve track quality, we extend previous tracking approaches by investigating human cognitive-level fusion for constraining the set of plausible targets where the number of targets is not known a priori. The target track algorithm predicts a belief in the position and pose for a set of targets and an automatic target recognition algorithm uses the pose estimate to calculate an accumulated target-belief classification confidence measure. The human integrates the target track information and classification confidence measures to determine the number and identification of targets. This paper implements the cognitive belief filtering approach for sensor fusion and resolves target identify through a set-theory approach by determining a plausible set of targets being tracked.

关键词： sensor fusion target recognition classification & identification tracking cognitive belief filter HRR

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Information fusion benefits delineation in off-nominal scenarios

Information fusion benefits delineation in off-nominal scena...

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Conference on sensor fusion - architectures, algorithms, and applications iii

作者： Dasarathy, BV Dynet Inc Huntsville AL 35814 USA

ISBN: (纸本)0819431931

The potential problem of deterioration In recognition system performance because of imprecise, incomplete, or imperfect training is a serious challenge inherent to most real-world applications. This problem is often referred to in certain applications as degradation of performance under off-nominal conditions. This study presents the results of an investigation carried out to illustrate the scope and benefits of information fusion in such off-nominal scenarios. The research covers features in - decision out (FEI-DEO) fusion as well as decisions in - decision out (DEI-DEO) fusion. The latter spans across both information sources (sensors) and multiple processing tools (classifiers). The investigation delineates the corresponding fusion benefit domains using as an example, real-world data from an audio-visual system for the recognition of French oral vowels embedded in various levels of acoustical noise.

关键词： information fusion off-nominal scenarios audio-visual fusion vowel recognition

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Cross band pixel selection in multi-resolution image fusion

Cross band pixel selection in multi-resolution image fusion

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Conference on sensor fusion - architectures, algorithms, and applications iii

作者： Petrovic, V Xydeas, C Univ Manchester Manchester Sch Engn MARC Manchester M13 9PL Lancs England

ISBN: (纸本)0819431931

The work described in this paper focuses on cross band pixel select:ion as applied to pixel level multi-resolution image fusion. In addition, multi-resolution analysis and synthesis is realised via. QMF sub-band decomposition techniques. Thus cross-band pixel selection is-considered with the aim of reducing the contrast and structural distortion image artefacts produced by existing wavelet based, pixel level, image fusion schemes. Preliminary subjective image fusion results demonstrate clearly the advantage which the proposed cross-band selection technique offers, when compared to conventional area based pixel selection.

关键词： image fusion multi-resolution image processing sensor fusion

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fusion of imaging and non-imaging sensor information for airborne surveillance

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proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 126-138页

作者： Valin, Pierre Jouan, Alexandre Bosse, Eloi Lockheed Martin Canada Montreal Canada

This paper presents results from an Adaptable Data fusion Testbed (ADFT) which has been constructed to analyze simulated or real data with the help of modular algorithms for each of the main fusion functions and image interpretation algorithms. The results obtained from data fusion of information coming from an imaging Synthetic Aperture Radar (SAR) and non-imaging sensors (ESM, IFF, 2-D radar) on-board an airborne maritime surveillance platform are presented for two typical scenarios of Maritime Air Area Operations and Direct Fleet Support. An extensive set of realistic databases has been created that contains over 140 platforms, carrying over 170 emitters and representing targets from 24 countries. A truncated Dempster-Shafer evidential reasoning scheme is used that proves robust under countermeasures and deals efficiently with uncertain, incomplete or poor quality information. The evidential reasoning scheme can yield both single ID with an associated confidence level and more generic propositions of interest to the Commanding Officer. For nearly electromagnetically silent platforms, the Spot Adaptive mode of the SAR, which is appropriate for naval targets, is shown to be invaluable in providing long range features that are treated by a 4-step classifier to yield ship category, type and class. Our approach of reasoning over attributes provided by the imagery will allow the ADFT to process in the next phase (currently under way) both FLIR imagery and SAR imagery in different modes (RDP for naval targets, Strip Map and Spotlight Non-Adaptive for land targets).

关键词： sensor data fusion

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Adaptive data fusion using the expected output membership function

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proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 26-33页

作者： Choi, Jongbae Dickerson, Julie A. Iowa State Univ United States

Fuzzy set methods can improve the fusion of uncertain sensor data. The expected output membership function (EOMF) method uses the fuzzified inputs and possible fuzzy outputs to estimate the fused output. The most likely fuzzy output comes from fusability measures which are calculated using the degrees of the intersections of the possible fuzzy outputs with the fuzzified inputs. The support lengths of the fuzzified inputs can be set proportional to the sensor variance in the fixed case. However, individual measurements can deviate widely from the true value even in accurate sensors. The support length of input sets can be varied by estimating the variation of the input. This adaptation helps deal with occasional bad or noisy measurements. The variation is defined as the absolute change rate of the input with respect to previous output estimates. The EOMF can also be too wide or too narrow compared to the fuzzified inputs. Adaptive methods can help select the size of the EOMF. An example from the control of automated vehicles shows the effectiveness of the adaptive EOMF method, compared to the fixed EOMF method and the weighted average method. The EOMF method shows robustness to outlying measurements when the average fusion operator is used.

关键词： sensor data fusion

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ELIPS: toward a sensor fusion processor on a chip

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proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 209-219页

作者： Daud, Taher Stoica, Adrian Thomas, Tyson Li, Wei-te Fabunmi, James California Inst of Technology Pasadena United States

The paper presents the concept and initial tests from the hardware implementation of a low-power, high-speed reconfigurable sensor fusion processor. The Extended Logic Intelligent Processing System (ELIPS) processor is developed to seamlessly combine rule-based systems, fuzzy logic, and neural networks to achieve parallel fusion of sensor in compact low power VLSI. The first demonstration of the ELIPS concept targets interceptor functionality; other applications, mainly in robotics and autonomous systems are considered for the future. The main assumption behind ELIPS is that fuzzy, rule-based and neural forms of computation can serve as the main primitives of an 'intelligent' processor. Thus, in the same way classic processors are designed to optimize the hardware implementation of a set of fundamental operations, ELIPS is developed as an efficient implementation of computational intelligence primitives, and relies on a set of fuzzy set, fuzzy inference and neural modules, built in programmable analog hardware. The hardware programmability allows the processor to reconfigure into different machines, taking the most efficient hardware implementation during each phase of information processing. Following software demonstrations on several interceptor data, three important ELIPS building blocks (a fuzzy set preprocessor, a rule-based fuzzy system and a neural network) have been fabricated in analog VLSI hardware and demonstrated microsecond-processing times.

关键词： Computer hardware

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MathWeb™:: A concurrent image analysis tool suite for multi-spectral data fusion

MathWeb™:: A concurrent image analysis tool suite for multi...

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Conference on sensor fusion - architectures, algorithms, and applications iii

作者： Achalakul, T Haaland, PD Taylor, S Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA

ISBN: (纸本)0819431931

This paper describes a preliminary approach to the fusion of multi-spectral image data for the analysis of cervical cancer. The long-term goal of this research is to define spectral signatures and automatically detect cancer cell structures. The approach combines a multi-spectral microscope with an image analysis tool suite, MathWeb. The tool suite incorporates a concurrent Principal Component Transform (PCT) that is used to fuse the multi-spectral data. This paper describes the general approach and the concurrent PCT algorithm. The algorithm is evaluated from both the perspective of image quality and performance scalability.

关键词： concurrent computing image fusion principal component transform spectral signature

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