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

作者： Penny, DE Def Evaluat & Res Agcy Malvern WR14 3PS Worcs England

ISBN: (纸本)0819431931

The Multi-sensor fusion Management (MSFM) algorithm positions multiple, detection-only, passive sensors in a two-dimensional plane to optimise the fused probability of detection using a simple decision fusion method, previously the MSFM algorithm was evaluated on two synthetic problem domains comprising of both static and moving targets(1). In the original formulation the probability distribution of the target location was modelled using a non-parametric approach. The logarithm of the fused detection probability was used as a criterion function for the optimisation of the sensor positions. This optimisation used a straightforward gradient ascent approach, which occasionally found local optima. Following the placement optimisation the sensors were deployed and the individual sensor detections combined using a logical OR fusion rule. The target location distribution could then be updated using the method of sampling, importance re-sampling (SIR). In the current work the algorithm is extended to admit a richer variety of behaviour. More realistic sensor characteristic models are used which include detection-plus-bearing sensors and false alarm probabilities commensurate with actual sonar sensor systems. In this paper the performance of the updated MSFM algorithm is illustrated on a realistic anti-submarine warfare (ASW) application(2) in which the placement of the sensors is carried out incrementally, allowing for the optimisation of both the location and the number of sensors to be deployed.

关键词： sensor fusion resource allocation anti-submarine warfare (ASW)

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

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 351-358页

作者： Achalakul, Tiranee Haaland, Peter D. Taylor, Stephen Syracuse Univ Syracuse United States

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： Image analysis

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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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PCA and wavelet transform for fusing panchromatic and multi-spectral images

PCA and wavelet transform for fusing panchromatic and multi-...

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

作者： Li, J Zhou, YQ Li, DR Wuhan Tech Univ Surveying & Mapping LIESMARS Wuhan 430070 Peoples R China

ISBN: (纸本)0819431931

Facing the increasing availability of remote sensing imagery, the compression of information and the combining of multi-spectral and multi-sensor image data are becoming of greater importance. This paper presents a new image fusion scheme based on PCA and multi-resolution analysis of wavelet theory for fusing high-resolution panchromatic and multi-spectral images. It is done in two ways: a). By replacing some wavelet coefficients of k-principal components by the corresponding coefficients of the high-resolution panchromatic image;b). By adding the wavelet coefficients of the high-resolution panchromatic image directly to k-principal components. The proposal approach is used to fuse the SPOT panchromatic and Landsat (TM) multi-spectral images. Experimental results demonstrate that the proposal approach can not only preserve all the spectral characteristics of the multi-spectral images, but can also improve their definition and spatial quality. Compared with the PCA fusion method, the proposal scheme is much better and possesses more capable of adaptability.

关键词： PCA the wavelet planes image merging substitution fusion additive 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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Convex optimization approach to the fusion of identity information

Convex optimization approach to the fusion of identity infor...

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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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sensor fusion with application to Electronic Warfare

Sensor fusion with application to Electronic Warfare

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

作者： Zanzalari, RM van Alstine, E Night Vis & Elect Sensors Directorate AMSEL RD NVS CCD Ft Monmouth NJ 07703 USA

ISBN: (纸本)0819431931

The Night vision and Electronic sensors Directorate, Survivability/Camouflage, Concealment and Deception Division mission is to provide affordable aircraft and ground electronic sensors/systems and signature management technologies which enhance survivability and lethality of U.S. and International Forces. Since 1992, efforts have been under tah-en in the area of Situational Awareness and Dominant Battlespace Knowledge. These include the Radar Deception and Jamming Advanced Technology Demonstration (ATD), Survivability and Targeting System Integration, Integrated Situation Awareness and Targeting ATD, Combat Identification, Ground vehicle Situational Awareness, and Combined Electronic Intelligence (ELINT) Target Correlation. This paper will address the Situational Awareness process as it relates to the integration of Electronic Warfare (EW) with targeting and intelligence and information warfare systems. Discussion will be presented on the sensor fusion, Situation Assessment and Response Management Strategies. sensor fusion includes the association, correlation, and combination of data and information from single and multiple sources to achieve refined position and identity estimates, and complete and timely assessments of situations and threats as well as their significance. Situation Assessment includes the process of interpreting and expressing the environment based on situation abstract products and information fi om technical and doctrinal data bases. Finally, Response Management provides the centralized, adaptable control of all renewable and expendable countermeasure assets resulting in optimization of the response to the threat environment.

关键词： Electronic Warfare sensors sensor data fusion Situational Awareness situation assessment Response Management association and correlation

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Adaptive data fusion using the expected output membership function

Adaptive data fusion using the expected output membership fu...

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

作者： Choi, JB Dickerson, JA Iowa State Univ Dept Elect & Comp Engn Ames IA 50011 USA

ISBN: (纸本)0819431931

关键词： data fusion fuzzy sets fuzzy systems neuro-fuzzy control

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

Fusion of imaging and non-imaging sensor information for air...

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

作者： valin, P Jouan, A Bossé, E Lockheed Martin Canada Montreal PQ H4P 1K6 Canada

ISBN: (纸本)0819431931

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： imaging non-imaging Dempster-Shafer testbed evidential reasoning maritime surveillance

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