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检索条件"任意字段=Conference on Sensor Fusion - Architectures, Algorithms, and Applications VI"

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Intelligent fusion processing in BMD applications

Intelligent fusion processing in BMD applications

引用

conference on sensor fusion - architectures, algorithms, and applications

作者： McCullough, C Byrd, K Bjork, C Grider, G Smith, B Morris, N Dasarathy, B U.S. Army Space and Strategic Defense Command (United States) Nichols Research Corp. (United States) Dynetics Inc. (United States)

ISBN: (纸本)081942482X

Intelligent processing techniques are applied to a Ballistic Missile Defense (BMD) application, focused on classifying the objects in a typical threat complex, using fused IR and Ladar sensors. These techniques indicate the potential to improve designation robustness against ''off-normal''/unexpected conditions, or when sensor data or classifier performance degrades. A Fused sensor Discrimination (FuSeD) simulation testbed was assembled for designation experiments, to evaluate test and simulation data, assess intelligent processor and classification algorithms, and evaluate sensor performance. Results were produced for a variety of neural net and other nonlinear classifiers, yielding high designation performance and low false alarm rates. Most classifiers yield a few percent in false alarm rate: rates are further improved when multiple techniques are applied via a Majority Based fusion technique. Example signatures, features, classifier descriptions, intelligent controller design, and architecture ate included. Work was performed for the Discriminating Interceptor Technology Program (DITP).

关键词： sensors LIDAR Intelligent sensors Neural networks Data fusion Doppler effect Computer simulations Detection and tracking algorithms Infrared sensors Infrared signatures

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A linearly constrained least squares approach for multisensor data fusion

A linearly constrained least squares approach for multisenso...

引用

conference on sensor fusion - architectures, algorithms, and applications

作者： Zhou, YF Leung, H Telexis Corporation Canada Ottawa ON K1V 7P2 2427 Holly Lane Canada Surface Radar Section Defence Research Establishment Ottawa Ottawa ON K1A OK2 Canada

ISBN: (纸本)081942482X

In this paper, we present a linearly constrained least squares (LCLS) algorithm for multisensor data fusion. While fusion is considered in the scope of linear combination, the objective of the LCLS algorithm is to minimize the energy of the linearly fused information based on empirical sensory information. Statistical performance analysis of the LCLS algorithm will be carried out including the consistency and asymptotic covariance of the estimates. Effectiveness of the proposed fusion algorithm will be evaluated numerically based on fusion of signals and images.

关键词： data fusion least squares minimum variance information uncertainty multisensor tracking consistency analysis

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fusion of imaging and non-imaging data for surveillance aircraft

Fusion of imaging and non-imaging data for surveillance airc...

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conference on sensor fusion - architectures, algorithms, and applications

作者： Shahbazian, E Gagnon, L Duquet, JR Macieszczak, M Valin, P Lockheed Martin Canada (Canada)

ISBN: (纸本)081942482X

This paper describes a phased incremental integration approach for application of image analysis and data fusion technologies to provide automated intelligent target tracking and identification for Airborne Surveillance on board an Aurora Maritime Patrol Aircraft. The sensor suite of the Aurora consists of a radar, an Identification Friend or Foe (IFF) system, an Electronic Support Measures (ESM) system, a Spotlight Synthetic Aperture Radar (SSAR), a Forward Looking Infra-Red (FLIR) sensor and a Link-11 tactical datalink system. Lockheed Martin Canada (LMCan) is developing a testbed, which will be used to analyze and evaluate approaches for combining the data provided by the existing sensors, which were initially not designed to feed a fusion system. Three concurrent research proof-of-concept activities provide techniques, algorithms and methodology into three sequential phases of integration of this testbed. These activities are: (a) analysis of the fusion architecture (track/contact/hybrid) most appropriate for the type of data available, (b) extraction and fusion of simple features from the imaging data into the fusion system performing automatic target identification, and (c) development of a unique software architecture which will permit integration and independent evolution, enhancement and optimization of various decision aid capabilities, such as Multi-sensor Data fusion (MSDF), Situation and Threat Assessment (STA) and Resource Management (RM).

关键词： intelligent decision aids data fusion image analysis automatic target recognition real-time adaptive planning situation and threat assessment resource management

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Asymmetric fusion strategies for target detection in multisensor environments

Asymmetric fusion strategies for target detection in multise...

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conference on sensor fusion - architectures, algorithms, and applications

作者： Dasarathy, BV Dynetics Inc. (United States)

ISBN: (纸本)081942482X

Most of the studies reported in the open literature on sensor fusion for target detection in multisensor environments have proposed fusion strategies that are essentially independent of the identity of the object as observed by the individual sensors. This independence makes the fusion strategies symmetric relative to the identity of the objects in terms of their target or non-target (decoys, clutter etc.) status. In this study, new ground is broken in terms of fusion strategies which, by being dependent on the identity of the objects as perceived by the individual sensors, can be asymmetric relative to the identity of the object under observation. The study analyzes the scope for and benefits of deployment of these asymmetric fusion strategies as compared to the conventional Boolean logic based symmetric fusion strategies studied previously. Under these conventional fusion strategies, while use of the Boolean AND logic for fusion tends to minimize the false alarm rate, use of OR logic maximizes the detection probability. Under the asymmetric fusion strategies conceived here, it is possible to drive the decision process towards maximizing the probability of detection of lethal objects (targets) while simultaneously minimizing the false alarm rates. The performance of these asymmetric fusion strategies, when embedded in a recursive structure that permits multiple observation and temporal fusion along the time line, are analyzed relative to that of the conventional symmetric fusion strategies to parametrically determine their domains of beneficial deployment.

关键词： sensor fusion temporal fusion decision fusion asymmetric fusion strategies Boolean logic based fusion

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Formal methods of automated reasoning for situational estimation

Formal methods of automated reasoning for situational estima...

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conference on sensor fusion - architectures, algorithms, and applications

作者： Llinas, J SUNY/Buffalo (United States)

ISBN: (纸本)081942482X

Most research and prototype development of automated methods for situational estimation in the data fusion community have applied heuristic approaches coupled to techniques for uncertainty management. Reasoning theorists would label these methods as those of the parametric reasoning class. Such methods are reasonable when the so-called ''closed world'' assumption can be confidently applied (ability to full prespecify expected conditions) which might have been reasonable in the ''Soviet Era'' but would appear fragile/brittle for current-day application. Motivated in part by these considerations and by the need to consider much more cost-effective knowledge-based-system development in an era of declining budgets, this paper offers some discussion on the applicability of more formal methods of reasoning for KBS. It is concluded that strictly formal methods for real-world applications require yet further theoretical development but that movement toward formalization is possible.

关键词： automated reasoning data fusion information fusion formal methods truth maintenance default reasoning

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Three dimensional data fusion for biomedical surface reconstruction

Three dimensional data fusion for biomedical surface reconst...

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conference on sensor fusion - architectures, algorithms, and applications

作者： Zachary, JM Iyengar, SS Louisiana State Univ. (United States)

ISBN: (纸本)081942482X

Traditional surface reconstruction techniques have focused exclusively on contour sections in one anatomical direction. However, in certain medical situations, such as in presurgical planning and radiation treatment, medical scans are taking of the patient in three orthogonal directions to better localize pathologies. fusion techniques must be used to register this data with respect to a surface fitting method. We explore the issues involved in fusing data from ellipsoid anatomy, such as the brain, heart, and major organs. The output of the fusion process is a set of data points which are correlated to one another to represent the surface of a single object. This data network is then used as input to a surface fitting algorithm which depends on two sampling metrics which we derive. The solution to this problem is important in presurgical planning, radiation treatment, and telemedical systems.

关键词： data fusion contour reconstruction surface reconstruction scattered data

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fusion-based methods for target identification in the absence of quantitative classifier confidence

Fusion-based methods for target identification in the absenc...

引用

conference on Signal Processing, sensor fusion, and Target Recognition vi

作者： Llinas, J SUNY/Buffalo (United States)

ISBN: (纸本)0819424838

In an era of reduced defense budgets, there is increased pressure to reuse any available technology or capability to the extent possible. For data fusion applications, this requirement can lead to situations where the output of disparate individual algorithms would like to be fused;ideally, this would be done in the most quantitative way possible. This paper reviews, integrates, and comments on various prior works in both the data fusion, remote sensing, and character recognition communities which are helpful to the data fusion algorithm/process designer dealing, in particular, with target identification and classification problems. It is shown that generalized voting and rank-based methods may be useful in these cases;the issue of source reliability is also addressed and methods for incorporating assigned reliabilities are described.

关键词： data fusion sensor fusion target identification target classification ranking methods voting methods

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fusion rule estimation using vector space methods

Fusion rule estimation using vector space methods

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conference on sensor fusion - architectures, algorithms, and applications

作者： Rao, NSV Oak Ridge National Lab. (United States)

ISBN: (纸本)081942482X

In a system of N sensors, the sensor S-j, j = 1,2...,N, outputs Y-(j) is an element of R, according to an unknown probability distribution P-Y(j/X);corresponding to input X is an element of [0.1]. A training n-sample (X-1, X-1), (X-2, Y-2), ...((X)n, Y-n) is given where Y-i = (Y-i((1)), Y-i((2)),...,Y-i((N))) such that Y-i((j)) is the output of S-j in response to input X-i. The problem is to estimate a fusion rule f: R-N proves [0.1], based on the sample, such that the expected square error is minimized over a family of function F that constitute a vector space. The function f* that minimizes the expected error cannot be computed since the underlying densities are unknown, and only an approximation (f) over cap to f* is feasible. We estimate the sample size sufficient to ensure that f provides a close approximation to f* with a high probability. The advantage of vector space methods are two-fold: (a) the sample size estimate is a simple function of the dimensionality of f and (b) the estimate (f) over cap can be easily computed by well-known least square methods in polynomial time. The results are applicable to the classical potential function methods and also (to a recently proposed) special class of sigmoidal feedforward neural networks.

关键词： sensor fusion fusion rule estimation empirical estimation vector space methods

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A novel architecture for expert assisted decision level fusion

A novel architecture for expert assisted decision level fusi...

引用

conference on sensor fusion - architectures, algorithms, and applications

作者： Williams, A Pachowicz, P Ronk, L SAIC Arlington VA 22203 4001 N. Fairfax Dr. United States George Mason University Systems Engineering Dept. Fairfax VA 22030 4400 University Dr. United States

ISBN: (纸本)081942482X

In this paper, we discuss a new fusion architecture, including some preliminary results on field data. The architecture consists of a new decision level fusion algorithm, the Piecewise Level fusion Algorithm (PLFA), integrated with a new expert system based user assistant that adjusts PLFA parameters to optimize for a user desired classification performance. This architecture is applicable for both multisensor and multilook fusion. The user specifies classification performance by inputting entries for a desired confusion matrix at the fusion center. The intelligent assistant suggests input alternatives to reach the performance goal based on previously supplied user inputs and on performance specifications of the individual sensors. If deadlock results, i.e., the goal is not attainable because of conflicting user inputs, the assistant Rill inform the user. As the user and assistant interact, the assistant calculates the parameters necessary to automatically adjust the PLFA for the required performance. These parameters and calculations are hidden from the user. That is, the architecture is designed so that user inputs are intuitive for an unskilled operator. The implementation of this adaptable fusion architecture is due to the relatively simple structure of the PLFA and the expert system heuristic rules. We briefly describe the PLFA structure and operation, illustrate some expert system rules, and discuss preliminary performance of the entire architecture, including a sample dialog between the user and the intelligent assistant. We conclude this paper with a discussion of future extensions to this architecture that include replacing human interactions with dynamic learning techniques.

关键词： multi-sensor fusion multi-look fusion expert assistant decision level fusion adaptive systems fusion architecture

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Gyroscopic data fusion via a quaternion based complementary filter

Gyroscopic data fusion via a quaternion based complementary ...

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conference on sensor fusion - architectures, algorithms, and applications

作者： Smith, R Frost, A Probert, P Oxford Univ. (UK) and Silsoe Research Institute (United Kingdom) Silsoe Research Institute (United Kingdom) Oxford Univ. (United Kingdom)

ISBN: (纸本)081942482X

We present an application of a complementary filter system to the attitude determination of a remotely operated underwater vehicle (ROV). The main contribution of this paper is to combine existing complementary filter theory with quaternion attitude representation. The combination allows accurate attitude determination by a real-time system using low cost sensors. We fuse the estimate from an Extended Kalman Filter (EKF) with the output from a set of vibrating structure rate gyroscopes. The EKF supplies high-quality low frequency information, the gyroscopes supply corresponding high frequency information. The attitude is described via a quaternion representation. We discuss how the use of quaternions is beneficial for estimator design due to the low computational burden, and lack of discontinuities and singularities. The EKF combines the output from two inclinometers and a magnetometer with a vehicle process model. The EKF assumes that sensor and process noise is broadband and that the process model captures all the important dynamics. An underwater vehicle is capable of rapid rotations, which are difficult to model, and would require computationally unattainable update rates to track effectively. We develop a filter, which uses the difference between the EKF and gyroscopic attitude estimates (an indirect filter) to correct for drift in the gyroscopic attitude estimate. We develop first a feedforward and then a feedback filter. The simplicity of the indirect filter permits very fast update rates, so the system may follow rapid vehicle rotations. We discuss the real-time implementation of the estimator on a Transputer based system mounted within a small ROV. We present experimental results showing the system performance of the combined filter system.

关键词： gyroscopes indirect filter data fusion quaternion estimation

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