Fuzzy logic data correlation approach in multisensor-multitarget tracking systems
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Authors
Aziz, Ashraf M.
Tummala, Murali
Cristi, Roberto
Advisors
Second Readers
Subjects
Data correlation
Data association
Tracking systems
Data fusion
Data association
Tracking systems
Data fusion
Date of Issue
1999
Date
Publisher
Elsevier
Language
Abstract
In this paper, a fuzzy logic data correlation approach for multisensor-multitarget tracking is proposed. This fuzzy correlation approach is developed based on fuzzy clustering means algorithm. The proposed approach is applied to a two- and a four-dimensional multisensor-multitarget tracking system using Monte Carlo simulations. Fuzzy system performance evaluation is presented to demonstrate the efficiency of the new approach. The computational complexity of this approach is also analyzed and compared to that of conventional fuzzy logic data association methods. Considerable improvement in terms of computational complexity and performance is achieved.
Type
Article
Description
Series/Report No
Department
Electrical and Computer Engineering
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funding
Format
15 p.
Citation
A.M. Ashraf, M. Tummala, R. Cristi, "Fuzzy logic data correlation approach in multisensor-multitarget tracking systems," Signal Processing, v. 76 (1999), pp. 195-209.
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
