Improving Ship Detection Based on Decision Tree Classification for High Frequency Surface Wave Radar

نویسندگان

چکیده

The traditional constant false alarm rate (CFAR) method, with fixed parameter settings and single noise background calculation, is unable to intelligently catch the current detection background. To improve performance of CFAR this paper proposes a target method based on decision tree classification (DTC) for high-frequency surface wave radar (HFSWR). Firstly, training sample set labels are obtained by means ship automatic identification system (AIS). Then, feature vector range dimension, Doppler dimension range-Doppler (RD) extracted way cell averaging, ordered statistics, censored mean trimmed mean. Finally, DTC used recognize “true” “false” targets in space. Experimental results show that, under same number targets, superior methods, accuracy can be increased more than 5%.

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ژورنال

عنوان ژورنال: Journal of Marine Science and Engineering

سال: 2023

ISSN: ['2077-1312']

DOI: https://doi.org/10.3390/jmse11030493