This study aims to present a sequential method for the classification of the autoregressive processes. Different from the conventional detectors having fixed sample size, the method uses Wald&rsquo / s sequential probability ratio test and has a variable sample size. It is shown that the suggested method produces the classification decisions much earlier than fixed sample size alternative on the average. The proposed method is extended to the case when processes have unknown variance. The effects of the unknown process variance on the algorithmperformance are examined. Finally, the suggested algorithm is applied to the classification of fixed and
rotary wing targets. The average detection time and its relation with signal to noise ratio are examined.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12613722/index.pdf |
| Date | 01 September 2011 |
| Creators | Otlu, Gunes |
| Contributors | Candan, Cagatay |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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