Research Article
Floating Small Target Detection in Sea Clutter Based on Jointed Features in FRFT Domain
@INPROCEEDINGS{10.1007/978-3-030-36405-2_14, author={Yan-ling Shi and Xue-liang Zhang and Zi-peng Liu}, title={Floating Small Target Detection in Sea Clutter Based on Jointed Features in FRFT Domain}, proceedings={Advanced Hybrid Information Processing. Third EAI International Conference, ADHIP 2019, Nanjing, China, September 21--22, 2019, Proceedings, Part II}, proceedings_a={ADHIP PART 2}, year={2019}, month={11}, keywords={Fractional Fourier Transform Jointed features Convex hull training algorithm Target detection Sea clutter}, doi={10.1007/978-3-030-36405-2_14} }- Yan-ling Shi
Xue-liang Zhang
Zi-peng Liu
Year: 2019
Floating Small Target Detection in Sea Clutter Based on Jointed Features in FRFT Domain
ADHIP PART 2
Springer
DOI: 10.1007/978-3-030-36405-2_14
Abstract
The jointed-feature detector for the floating small target in sea clutter is addressed in the paper. For the traditional energy-based detectors, it is difficult to detect the low signal-to-clutter ratio floating small target in time domain due to the affection of sea clutter motion. Therefore, a feature detector in the Fractional Fourier transform (FRFT) domain is proposed. The Hurst exponent and fractal dimension variance are extracted as the features in the jointed-feature detector in FRFT domain. The decision region is determined by convex hull training algorithm on the given false alarm probability. The experimental results of 10 groups of IPIX radar data show that the jointed-feature detector is superior to the compared one, and it provides a new detection scheme for radar target detection.
