A comparison on information fusion methods for air target identification

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A comparison on information fusion methods for air target identification

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Symposium on Applied Computing archive
Proceedings of the 2005 ACM symposium on Applied computing table of contents

Santa Fe, New Mexico

SESSION: AI and computational logic and image analysis (AI): poster papers table of contents

Pages: 45 - 46

Year of Publication: 2005

ISBN:1-58113-964-0

Authors

Dongseob Jang	McMaster University, Hamilton
Sung Y. Shin	South Dekota State University
Charlie Y. Shim	South Dekota State University
C. C. Hung	Southern Polytechnic State University, Marietta, GA

Sponsor

SIGAPP: ACM Special Interest Group on Applied Computing

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 6, Downloads (12 Months): 23, Citation Count: 0

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abstract references index terms collaborative colleagues

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ABSTRACT

We compared the performance of Bayes Theory, Fuzzy Set Theory, Heuristic method and Dempster-Shafer Theory in the identification of aircrafts by using the information from different sensors. From the results of the simulation, the Fuzzy method produces the best result. The final identification could be improved if specific features of each type of aircraft are available. To get more accurate object identification, the results from each method can be combined with the best assignment of values for each method.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Air force research laboratory technology "Battlespace Awareness through Information Fusion". Retrieved February 2004 from <u>http://www.afrlhorizons.com/</u>
	2	Steven L. Tanimoto, The elements of artificial intelligence: an introduction using LISP, Computer Science Press, Inc., New York, NY, 1987
	3	Edward Walt, Jame Llinas, Multisensor Data Fusion, Artech House; Boston, London, 1991.
	4	Yaakkov Bar-Shalon, MultiTarget-MultiSensor Tracking: Application and Advances, Vol II, Artech House, 1992.
	5	David Hall and Sonya McMullen, Mathematical Techniques in Multisensor Data Fusion, Artech House, March 2004.
	6	Dong-Seob Jang, Information Fusion Methods for Air Target Identification, MS thesis, Department of Computer Science and Electrical Engineering, South Dakota State University, May 2004.

INDEX TERMS

Keywords:
bayes theory, dempster-shafer theory, fuzzy set, information fusion

Collaborative Colleagues:

Dongseob Jang: colleagues

Sung Y. Shin: colleagues

Charlie Y. Shim: colleagues

C. C. Hung: colleagues

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