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Robust CFAR Detector Based on Truncated Statistics in Multiple-Target Situations.
- Source :
-
IEEE Transactions on Geoscience & Remote Sensing . Jan2016, Vol. 54 Issue 1, p117-134. 18p. - Publication Year :
- 2016
-
Abstract
- A new and robust constant false alarm rate (CFAR) detector based on truncated statistics (TSs) is proposed for ship detection in single-look intensity and multilook intensity synthetic aperture radar data. The approach is aimed at high-target-density situations such as busy shipping lines and crowded harbors, where the background statistics are estimated from potentially contaminated sea clutter samples. The CFAR detector uses truncation to exclude possible statistically interfering outliers and TSs to model the remaining background samples. The derived truncated statistic CFAR (TS-CFAR) algorithm does not require prior knowledge of the interfering targets. The TS-CFAR detector provides accurate background clutter modeling, a stable false alarm regulation property, and improved detection performance in high-target-density situations. [ABSTRACT FROM AUTHOR]
- Subjects :
- *RADAR
*DETECTORS
*QUANTITATIVE research
*REMOTE sensing
*EARTH sciences
Subjects
Details
- Language :
- English
- ISSN :
- 01962892
- Volume :
- 54
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Geoscience & Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 110902142
- Full Text :
- https://doi.org/10.1109/TGRS.2015.2451311