This thesis develops an algorithm to fuse redundant observations due to multiple sensor coverage of a vessel. Fuzzy membership functions are used as a measure of correlation, and a fuzzy associative system determines which observations represent the same vessel. The result is a computationally efficient algorithm. The output of the system is a unique set of vessels identified by unique platform identifiers. Results of tests based on computer simulation of overlapping radar coverage show that the fusion algorithm correctly correlates and fuses the sensor observations. That the VTS system is a subset of the Joint Maritime Command Information System (JMCIS) and ultimately the Global Command and Control Software (GCCS) system makes this algorithm pertinent not only to the US Coast Guard, but also to the US Navy, DOD and other agencies such as the Canadian Navy that use this software.
| Identifer | oai:union.ndltd.org:nps.edu/oai:calhoun.nps.edu:10945/31314 |
| Date | 12 1900 |
| Creators | Glenn, Ian Neil |
| Contributors | Tummala, Murali, Electrical Engineering |
| Publisher | Monterey, California. Naval Postgraduate School |
| Source Sets | Naval Postgraduate School |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
| Rights | This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, it may not be copyrighted. |
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