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.
This work was supported by National Natural Science Foundation of China (61201325) and NUPTSF (NY218045).
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References
You, H., Yong, H., Jian, G.: An overview on radar target detection in sea clutter. Mod. Radar 36(12), 1–9 (2014)
Ding, H., Dong, Y., Liu, N.: Overview and prospects of research on sea clutter property cognition. J. Radars 5(5), 499–516 (2016)
Xu, S., Zheng, J., Pu, J.: Sea-surface “floating small target detection based on polarization features”. IEEE Geosci. Remote Sens. Lett. 15(10), 1505–1509 (2018)
Li, D., Shui, P.: Floating small target detection in sea clutter via normalised Doppler power spectrum. IET Radar Sonar Navig. 10(4), 699–706 (2016)
Ye, Y., Hong, Z., Wang, Q.: Correlation feature-based detector for range distributed target in sea clutter. EURASIP J. Adv. Signal Process. 2018(1), 25 (2018)
Shi, Y., Xie, X., Li, D.: Distributed floating target detection in sea clutter via feature-based detector. IEEE Geosci. Remote Sens. Lett. 13(12), 1847–1850 (2016)
Shi, S., Shui, P.: Sea-surface floating small target detection by one-class classifier in time-frequency feature space. IEEE Trans. Geosci. Remote Sens. 56(11), 6395–6411 (2018)
Lo, T., Leung, H., Litva, J.: Fractal characterisation of sea-scattered signals and detection of sea-surface targets. In: IEEE Proceedings F Radar and Signal Processing, vol. 140, no. 4, pp. 243–250 (1993)
Li, D., Shui, P.: Extended fractal analysis for floating target detection in sea clutter. In: IEEE International Geoscience and Remote Sensing Symposium, pp. 3139–3142 (2015)
Chen, Y., Sun, R., Zhou, A.: An improved Hurst parameter estimator based on fractional Fourier transform. In: Proceedings of the ASME 2007 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, Las Vegas, Nevada, USA, pp. 1–11 (2007)
Guan, J., Liu, N., Zhang, J.: Multifractal correlation characteristic of real sea clutter and low-observable targets detection. J. Electron. Inf. Technol. 32(1), 54–61 (2010)
Hu, J., Gao, J., Yao, K.: Detection of low-observable targets within sea clutter by structure function based multifractal analysis. IEEE Trans. Antennas Propag. 54(1), 136–143 (2006)
Guan, J., Liu, N., Huang, Y.: Fractal characteristic in frequency domain for target detection within sea clutter. IET Radar Sonar Navig. 6(5), 293–306 (2012)
Chen, X., Guan, J., Bao, Z.: Detection and extraction of target with micromotion in spiky sea clutter via short-time Fractional Fourier Transform. IEEE Trans. Geosci. Remote Sens. 52(2), 1002–1018 (2014)
Guan, J., Liu, N., Zhang, J.: Low-observable target detection within sea clutter based on LGF. Signal Process. 26(1), 69–73 (2010)
Chen, X., Guan, J., He, Y.: Detection of low observable moving target in sea clutter via fractal characteristics in Fractional Fourier Transform domain. IET Radar Sonar Navig. 7(6), 635–651 (2013)
Xing, H., Zhang, Q., Xu, W.: Fractal property of sea clutter FRFT spectrum for small target detection. Acta Phys. Sin. 1, 1–8 (2015)
Shui, P., Li, D., Xu, S.: Tri-feature-based detection of floating small targets in sea clutter. IEEE Trans. Aerosp. Electron. Syst. 50(2), 1416–1430 (2014)
Haykin, S.: The McMaster IPIX radar sea clutter database in 1993. http://soma.mcmaster.ca/ipix.php
Li, Y., Lv, X., Liu, K.: Fractal-based weak target detection within sea clutter. Acta Ocean. Sin. 33(9), 68–72 (2014)
Xu, X.: Low observable targets detection by joint fractal properties of sea clutter: an experimental study of IPIX OHGR datasets. IEEE Trans. Antennas Propag. 58(4), 1425–1429 (2010)
Guan, J., Cheng, X., Huang, Y.: Adaptive Fractional Fourier Transform-based detection algorithm for moving target in heavy sea clutter. IET Radar Sonar Navig. 6(5), 389–401 (2012)
Xing, H., Yin, J., Wang, Q.: Targets detection under the background of sea clutter by joint characteristics difference. Mod. Radar 36(10), 28–32 (2014)
Shi, Y., Shui, P.: Feature united detection algorithm on floating small target of sea surface. J. Electron. Inf. Technol. 34(4), 871–877 (2012)
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Shi, Yl., Zhang, Xl., Liu, Zp. (2019). Floating Small Target Detection in Sea Clutter Based on Jointed Features in FRFT Domain. In: Gui, G., Yun, L. (eds) Advanced Hybrid Information Processing. ADHIP 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 302. Springer, Cham. https://doi.org/10.1007/978-3-030-36405-2_14
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