Formalizing classes of information fusion systems

This paper provides an outline of a formalization of classes of information fusion systems in terms of category theory and formal languages. The formalization captures both the inputs/outputs of a fusion system and the fusion processing algorithms. The paper also introduces a notion of subclass, which is used to compare classes of fusion systems, whether they are different or one is a special case of another. Two examples of classes of fusion systems formalized in the paper are data fusion and decision fusion; decision fusion is shown to be a subclass of data fusion. A number of other classes of fusion systems are defined. The formalization is extended by adding the notion of measure of effectiveness, which is then used to prove that one of the classes (so called overlapping system) is at least as efficient as a single-source system. And finally it is shown how data association can be formalized in this framework. While at first the formalization could be used by information fusion scientists to formally define various types of fusion systems and then to prove theorems about properties of such systems, it is expected that it should lead to the development of tools that could be used by software engineers to formally derive designs of fusion systems.

[1]  James J. Clark,et al.  Data Fusion for Sensory Information Processing Systems , 1990 .

[2]  James A. Hendler,et al.  The semantic Web and its languages , 2000 .

[3]  I. R. Goodman,et al.  Mathematics of Data Fusion , 1997 .

[4]  James Llinas,et al.  Multisensor Data Fusion , 1990 .

[5]  Alan N. Steinberg,et al.  Community Status Report and Proposed Revisions to the JDL Data Fusion Model , 1998 .

[6]  Jeannette M. Wing A specifier's introduction to formal methods , 1990, Computer.

[7]  Stelios C. A. Thomopoulos Sensor integration and data fusion , 1990, J. Field Robotics.

[8]  Benjamin C. Peirce,et al.  Basic Category Theory for Computer Scientists , 1991 .

[9]  Clark Adams Over the Horizon , 1976, Computer.

[10]  Alan N. Steinberg,et al.  Revisions to the JDL data fusion model , 1999, Defense, Security, and Sensing.

[11]  Mieczyslaw M. Kokar,et al.  A formal approach to the design of feature-based multi-sensor recognition systems , 2001, Inf. Fusion.

[12]  Donald Sannella,et al.  Essential concepts of algebraic specification and program development , 1997, Formal Aspects of Computing.

[13]  A.,et al.  A Formal Approach to Information Fusion , 1999 .

[14]  Paul S. Schenker Sensor fusion II: Human and machine strategies; Proceedings of the Meeting, Philadelphia, PA, Nov. 6-9, 1989 , 1990 .

[15]  James Llinas,et al.  An introduction to multisensor data fusion , 1997, Proc. IEEE.

[16]  Belur V. Dasarathy,et al.  Sensor fusion potential exploitation-innovative architectures and illustrative applications , 1997, Proc. IEEE.

[17]  Belur V. Dasarathy,et al.  Decision fusion , 1994 .

[18]  Scott A. DeLoach,et al.  Category Theory Approach to Fusion of Wavelet-Based Features , 1999 .

[19]  Pramod K. Varshney,et al.  Distributed Detection and Data Fusion , 1996 .

[20]  Lawrence A. Klein,et al.  Sensor and Data Fusion Concepts and Applications , 1993 .

[21]  Kuldeep Kumar,et al.  Strategies for incorporating formal specifications in software development , 1994, CACM.

[22]  Jake K. Aggarwal,et al.  Multisensor Fusion for Computer Vision , 1993, NATO ASI Series.

[23]  Edward R. Dougherty,et al.  Matrix Structured Image Processing , 1987 .

[24]  D. L. Hall,et al.  Mathematical Techniques in Multisensor Data Fusion , 1992 .

[25]  Sonya A. H. McMullen,et al.  Mathematical Techniques in Multisensor Data Fusion (Artech House Information Warfare Library) , 2004 .

[26]  Jorge Herbert de Lira,et al.  Two-Dimensional Signal and Image Processing , 1989 .

[27]  Yellamraju V. Srinivas Category Theory Definitions and Examples , 1990 .

[28]  Richard A. Kemmerer,et al.  Integrating formal methods into the development process , 1990, IEEE Software.

[29]  Chen C. Chang,et al.  Model Theory: Third Edition (Dover Books On Mathematics) By C.C. Chang;H. Jerome Keisler;Mathematics , 1966 .

[30]  Dou Long,et al.  Fusion of detection probabilities and comparison of multisensor systems , 1990, IEEE Trans. Syst. Man Cybern..

[31]  M. Kokar,et al.  Data vs. Decision Fusion in the Category Theory Framework , 2001 .

[32]  J. B. Hunter,et al.  Information properties as a means to define decision fusion methodologies in non-benign environments , 2003, Sixth International Conference of Information Fusion, 2003. Proceedings of the.