This paper describes a project that was sponsored by the U.S. Army Space and Strategic Defense Co... more This paper describes a project that was sponsored by the U.S. Army Space and Strategic Defense Command (USASSDC) to develop, test, and demonstrate sensor fusion algorithms for target recognition. The purpose of the project was to exploit the use of sensor fusion at all levels (signal, feature, and decision levels) and all combinations to improve target recognition capability against tactical
This paper describes a project that was sponsored by the U.S. Army Space and Strategic Defense Co... more This paper describes a project that was sponsored by the U.S. Army Space and Strategic Defense Command (USASSDC) to develop, test, and demonstrate sensor fusion algorithms for target recognition. The purpose of the project was to exploit the use of sensor fusion at all levels (signal, feature, and decision levels) and all combinations to improve target recognition capability against tactical
The concept of reciprocal relationship (RR) bonds, conceived and developed as a tool in the knowl... more The concept of reciprocal relationship (RR) bonds, conceived and developed as a tool in the knowledge discovery process, was reported and illustrated at this conference last year. Various distance metrics for measuring the distances in the database multi-dimensional attribute space were reviewed in this context identifying their relationship to the type of the attributes, depending on whether they are continuous valued, integer valued, or symbolic valued or a mix thereof. In this study, we explore the sensitivity of the bonding process to the metrics that are mostly suited to continuous valued attributes only, such as Euclidean, city-block, and chess board, using once again the previously used data set for illustrative purposes. This sensitivity to the metric employed is investigated at various stages of the RR bond delineation process. Results obtained under the different metrics are compared and fused to identify the degree of consensus that in turn can provide a measure of confidence in the results of the knowledge discovery process.
Handbook of Data Mining and Knowledge Discovery, 2002
Abstract This article elaborates on the role of neural networks in data mining, especially classi... more Abstract This article elaborates on the role of neural networks in data mining, especially classification, and presents various ways of using them in this area. In order to do this the main architectures of neural networks (including multilayer perceptrons and radial basis function networks) are reviewed, and an overview of the classification process and the training of neural networks is given. Furthermore, the interpretation of neural networks and the generation of rules based on already trained networks are discussed and exemplified ...
Critical elements of future exoatmospheric interceptor systems are intelligent processing techniq... more Critical elements of future exoatmospheric interceptor systems are intelligent processing 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 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. 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, classifies, or to request additional sensor data on specific objects that have not been confidently identified as 'lethal' or 'non-legal'. 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 interceptor applications.
This paper describes a project that was sponsored by the U.S. Army Space and Strategic Defense Co... more This paper describes a project that was sponsored by the U.S. Army Space and Strategic Defense Command (USASSDC) to develop, test, and demonstrate sensor fusion algorithms for target recognition. The purpose of the project was to exploit the use of sensor fusion at all levels (signal, feature, and decision levels) and all combinations to improve target recognition capability against tactical
This paper describes a project that was sponsored by the U.S. Army Space and Strategic Defense Co... more This paper describes a project that was sponsored by the U.S. Army Space and Strategic Defense Command (USASSDC) to develop, test, and demonstrate sensor fusion algorithms for target recognition. The purpose of the project was to exploit the use of sensor fusion at all levels (signal, feature, and decision levels) and all combinations to improve target recognition capability against tactical
The concept of reciprocal relationship (RR) bonds, conceived and developed as a tool in the knowl... more The concept of reciprocal relationship (RR) bonds, conceived and developed as a tool in the knowledge discovery process, was reported and illustrated at this conference last year. Various distance metrics for measuring the distances in the database multi-dimensional attribute space were reviewed in this context identifying their relationship to the type of the attributes, depending on whether they are continuous valued, integer valued, or symbolic valued or a mix thereof. In this study, we explore the sensitivity of the bonding process to the metrics that are mostly suited to continuous valued attributes only, such as Euclidean, city-block, and chess board, using once again the previously used data set for illustrative purposes. This sensitivity to the metric employed is investigated at various stages of the RR bond delineation process. Results obtained under the different metrics are compared and fused to identify the degree of consensus that in turn can provide a measure of confidence in the results of the knowledge discovery process.
Handbook of Data Mining and Knowledge Discovery, 2002
Abstract This article elaborates on the role of neural networks in data mining, especially classi... more Abstract This article elaborates on the role of neural networks in data mining, especially classification, and presents various ways of using them in this area. In order to do this the main architectures of neural networks (including multilayer perceptrons and radial basis function networks) are reviewed, and an overview of the classification process and the training of neural networks is given. Furthermore, the interpretation of neural networks and the generation of rules based on already trained networks are discussed and exemplified ...
Critical elements of future exoatmospheric interceptor systems are intelligent processing techniq... more Critical elements of future exoatmospheric interceptor systems are intelligent processing 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 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. 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, classifies, or to request additional sensor data on specific objects that have not been confidently identified as 'lethal' or 'non-legal'. 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 interceptor applications.
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