Data fusion architecture can be categorized into data-level fusion, feature-level fusion and decision-level fusion by its characteristics. In this paper, we provide a new target identification fusion technology in whi...
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ISBN:
(纸本)0819444812
Data fusion architecture can be categorized into data-level fusion, feature-level fusion and decision-level fusion by its characteristics. In this paper, we provide a new target identification fusion technology in which we adopt not only feature-level fusion approach but also decision-level fusion approach in order to consider even sensors' uncertain reports and improve fusion performance. In feature-level fusion stage, we applied fuzzy set theory and Bayesian theory based on the sensor data, such as sensor parameter and detected target information. In decision-level fusion stage, we applied advanced Bayesian theory to decide final target identification. Experimental results with various kinds of sensor data have verified the robustness of our algorithms comparing with conventional feature-level, decision-level fusion algorithms.
Various fusion system architectures postulated and studied previously for environments with two and three data sources are further explored in this study to bring out the expanding scope for delineating the architectu...
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ISBN:
(纸本)0819449598
Various fusion system architectures postulated and studied previously for environments with two and three data sources are further explored in this study to bring out the expanding scope for delineating the architecture options for multiple data source environments. A spectrum of single and multi-stage fusion architecture options are defined. The potential for such expansion of choices is illustrated using the scenario with four data sources as an example. Potential problem environments corresponding to this range of two to four data sources are identified. Various fusion logic strategies that can be brought to bear for the analysis of these fusion architecture options, when these fusionarchitectures are employed for Decisions In - Decision Out (DEI-DEO) fusion, are also discussed.
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.
This paper provides a description and detailed review of a multiple hypothesis tracking system, which handles data from two radars, and a number of other sources. An efficient method for processing detections from two...
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ISBN:
(纸本)081942482X
This paper provides a description and detailed review of a multiple hypothesis tracking system, which handles data from two radars, and a number of other sources. An efficient method for processing detections from two (time-offset) radars, and integrating them in the multiple hypothesis framework will be described. The implications of such a methodology on the tracking filter will also be discussed. The paper then explains the algorithm employed for fusion of Automatic Dependent Surveillance reports into the system, and concludes with a demonstration of some sample results.
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.
The Multi-sensorfusion Management (MSFM) algorithm is extended to admit a richer variety of behavior. More realistic sensor characteristic models are used such as detection-plus-bearing sensors and false alarm probab...
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The Multi-sensorfusion Management (MSFM) algorithm is extended to admit a richer variety of behavior. More realistic sensor characteristic models are used such as detection-plus-bearing sensors and false alarm probabilities commensurate with actual sonar sensor systems. The performance of the modified MSFM algorithm is illustrated on a realistic anti-submarine warfare (ASW) application.
Information fusion includes the integration of feature data, expert knowledge, and algorithms. For example, in automatic target recognition (ATR) features of size, color, and motion can be fused to assess the combinat...
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ISBN:
(纸本)0819436771
Information fusion includes the integration of feature data, expert knowledge, and algorithms. For example, in automatic target recognition (ATR) features of size, color, and motion can be fused to assess the combination of multi-modal information. A neurofuzzy fusion of features captures the multilevel language content of sensory information by fusing neural network data analysis with rule-based decision making. Additionally, the neurofuzzy architecture can effectively fuse coarse and fine abstracted feature data at the content level for decision making. In this paper, we investigate a multilevel neuro-fuzzy feature-based architecture for synthetic aperture radar (SAR) target recognition.
The next decade will require the development of complex sensor systems that integrate data from a large number of sensor elements. Such systems will play important roles in a wide variety of industrial and defense sys...
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ISBN:
(纸本)0819428256
The next decade will require the development of complex sensor systems that integrate data from a large number of sensor elements. Such systems will play important roles in a wide variety of industrial and defense systems, as the fusion of multiple sources of information is crucial to sensor operation in noisy environments, and in complex decision making. The arrival of ubiquitous processing elements is one requirement for the development of such systems;however, the ability to connect and integrate these elements at the logical level is the more limiting aspect of their development. Furthermore, it is unlikely that such systems can be developed in a single linear process. It is much more probable that such systems will need to be evolved over time, perhaps a substantial period of time, and as result the ability to logically interconnect heterogeneous elements in an evolutionary manner will be of great importance. This paper outlines some approaches to this problem based on the distributed object-computing model as introduced in the OMG CORBA. It is our belief that this technology is maturing to the point that it could form the foundations for a sensor architecture that would support the evolutionary development of complex sensor networks.
Intelligent Transportation Systems (ITS), implemented all over the world, has become an important and practical traffic management technique. Among all ITS subsystems, the detection system plays an integral element th...
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ISBN:
(纸本)0819431931
Intelligent Transportation Systems (ITS), implemented all over the world, has become an important and practical traffic management technique. Among all ITS subsystems, the detection system plays an integral element that provides all the necessary environmental information to the ITS infrastructure. This paper describes the ITS Detector testbed design, currently being implemented with these potential ITS applications on the State Highway 6 in College Station, Texas to provide a multi-sensor, multi-source fusion environment that utilizes both multi-sensor and distributed sensor system testing environment.
We discuss Virtual Associative Networks (VANs) and their relevance for addressing computationally prohibitive sensorfusion problems (with results in Dynamic sensor Management). To our knowledge, this discussion of VA...
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We discuss Virtual Associative Networks (VANs) and their relevance for addressing computationally prohibitive sensorfusion problems (with results in Dynamic sensor Management). To our knowledge, this discussion of VAN technology for sensorfusion 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.
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