A fuzzy logic based data association routine has been developed. The concept is based on very simple fuzzy logic implementation. The resulting technique is intended as an enhancement to current data association routin...
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A fuzzy logic based data association routine has been developed. The concept is based on very simple fuzzy logic implementation. The resulting technique is intended as an enhancement to current data association routines when added information such as sensor blockage and forbidden terrain knowledge can be incorporated into the system.
The Joint Directors of Laboratories (JDL) Data fusion Group's Data fusion Model is the most widely used method for categorizing data fusion-related functions. This model is modified to facilitate the cost-effectiv...
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The Joint Directors of Laboratories (JDL) Data fusion Group's Data fusion Model is the most widely used method for categorizing data fusion-related functions. This model is modified to facilitate the cost-effective development, acquisition, integration and operation of multi-sensor/multi-source systems. Proposed modifications include broadening of the functional model and related taxonomy beyond the original military focus, and integrating the Data fusion Tree Architecture model for system description, design and development.
A new track-to-track association algorithm mixing kinematics data provided by the radar and identification data provided by the Electronic Support Measure (ESM) sensor is presented. The performance of this algorithm i...
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A new track-to-track association algorithm mixing kinematics data provided by the radar and identification data provided by the Electronic Support Measure (ESM) sensor is presented. The performance of this algorithm is confirmed in terms of probability of correct association and probability of false association. This algorithm provides the double advantage of providing information about the common origin of the tracks and an identification of each track.
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 discrimin...
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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.
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 unresol...
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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.
We propose an unbiased multifeature fusion Pulse Coupled Neural Network (PCNN) algorithm. The method shares linking between several PCNNs running in parallel. We illustrate the PCNN fusion technique with a clean and n...
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We propose an unbiased multifeature fusion Pulse Coupled Neural Network (PCNN) algorithm. The method shares linking between several PCNNs running in parallel. We illustrate the PCNN fusion technique with a clean and noisy three-band color image example.
Availability of different imaging modalities requires techniques to process and combine information from different images of the same phenomena. We present a symmetry based approach for combining information from mult...
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Availability of different imaging modalities requires techniques to process and combine information from different images of the same phenomena. We present a symmetry based approach for combining information from multiple images. fusion is performed at data level. Actual object boundaries and shape descriptors are recovered directly from raw sensor output(s). Method is applicable to arbitrary number of images in arbitrary dimension.
The Dempster Shafer (DS) Theory of Evidential Reasoning may be useful in handling issues associated with theater ballistic missile discrimination. This paper highlights the Dempster-Shafer theory and describes how thi...
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The Dempster Shafer (DS) Theory of Evidential Reasoning may be useful in handling issues associated with theater ballistic missile discrimination. This paper highlights the Dempster-Shafer theory and describes how this technique was implemented and applied to data collected by two infrared sensors on a recent flight test.
In both military and civilian applications, increasing interest is being shown in fusing infrared and vision images for improved situational awareness. In previous work, the authors have developed a fusion method for ...
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ISBN:
(纸本)0819431931
In both military and civilian applications, increasing interest is being shown in fusing infrared and vision images for improved situational awareness. In previous work, the authors have developed a fusion method for combining the thermal and vision images into a single image emphasizing the most salient features of the surrounding environment. This approach is based on the assumption that although the thermal and vision data are uncorrelated, they are complementary and can be fused using a suitable disjunctive function. This paper, as a continuation of that work, will describe the development of an information based real-time data level fusion method. In addition, applicability of the algorithms thar we developed for data level fusion to feature level techniques (e.g., shapes, lines, and edges) will be investigated.
We propose an unbiased multifeature fusion Pulse Coupled Neural Network (PCNN) algorithm. The method shares linking between several PCNNs running in parallel. We illustrate the PCNN fusion technique with a clean and n...
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ISBN:
(纸本)0819431931
We propose an unbiased multifeature fusion Pulse Coupled Neural Network (PCNN) algorithm. The method shares linking between several PCNNs running in parallel. We illustrate the PCNN fusion technique with a clean and noisy three-band color image example.
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