| 摘要: |
| 低分辨雷达体制的限制和探测过程中背景杂波的影响，使得低分辨雷达飞机目标的分类识别较为困难。本文提出一种分数域多重分形方法，通过引入分数阶Fourier变换（FRFT）寻找飞机目标回波的最优FRFT域，并在最优分数阶FRFT域提取目标回波数据的多重分形特征，结合支持向量机进行飞机目标的分类识别。实验表明，FRFT可以增强飞机目标回波的多重分形特性；从最优FRFT域提取的多重分形特征具有较好的分类识别效果，FRFT域多重分形方法的飞机目标分类识别率要高于时域多重分形方法的飞机目标分类识别率；即使在低信噪比条件下，FRFT域多重分形方法仍可实现低分辨雷达飞机目标的粗分类。 |
| 关键词: 低分辨雷达 分数阶Fourier变换 多重分形 目标分类 |
| DOI：DOI:10.3969/j.issn.1672-2337.2019.06.010 |
| 分类号:TN957.51 |
| 基金项目:国家自然科学基金（No.61561004） |
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| Target Classification Based on Multifractal Features in Fractional Fourier Transform Domain |
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ZHANG Huaxia，LI Qiusheng
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1.Research Center of Intelligent Control Engineering Technology，Gannan Normal University，Ganzhou341000，China;2.School of Physics and Electronic Information，Gannan Normal University，Ganzhou341000，China
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| Abstract: |
| Due to the limitations of low resolution radar system and background clutter，the task of aircraft classification with low resolution radar is relatively difficult. This paper introduces fractional Fourier transform (FRFT) to process aircraft echoes，and further searches for the optimal FRFT domain where multifractal features of target echoes are extracted. Support vector machine is used for target classification. Experiments show that the multifractal characteristics of aircraft echoes can be enhanced by FRFT. The features extracted from the optimal FRFT domain can be used effectively to identify different types of aircraft. The classification and recognition rates of aircraft targets based on FRFT domain multifractal method is higher than that based on time domain multifractal method. The FRFT domain multifractal method can achieve rough classification of aircraft targets even under low signal to noise ratios (SNR). |
| Key words: low resolution radar fractional Fourier transform multifractal target classification |
