基于PACGAN与差分星座轨迹图的辐射源个体识别 |
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引用本文: | 牛伟宇,许华,刘英辉,秦博伟,史蕴豪. 基于PACGAN与差分星座轨迹图的辐射源个体识别[J]. 信号处理, 2021, 37(8): 1559-1567. DOI: 10.16798/j.issn.1003-0530.2021.08.024 |
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作者姓名: | 牛伟宇 许华 刘英辉 秦博伟 史蕴豪 |
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作者单位: | 空军工程大学信息与导航学院 |
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摘 要: | 深度学习解决个体识别的一个突出问题是难以获得足够样本对网络进行训练,针对该问题,提出了一种基于PACGAN(Pooling Auxiliary Classifier Generative Adversarial Network)的辐射源个体识别算法.该算法针对输入信号的差分星座轨迹图进行处理,并对辅助分类生成式对抗网(...
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关 键 词: | 个体识别 差分星座图轨迹图 生成式对抗网 池化操作 |
收稿时间: | 2021-03-04 |
Individual Identification Method based on PACGAN and Differential Constellation Trace Figure |
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Affiliation: | Information and Navigation College, Air Force Engineering University |
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Abstract: | One of the outstanding problems of applying deep learning to solve Individual Identification is that it is difficult to collect enough samples to train the network. In order to solve this problem, an individual identification algorithm based on PACGAN is proposed. The algorithm processes the Differential Constellation Trace Figure of input signals, and improves the adaptability of ACGAN. This paper improves the adaptability of ACGAN, introduces pooling layer in the discriminator network to enhance its feature extraction ability in multi classification task; for the situation of a large number of edge distribution of sample image features, adds zero filling layer and increases convolution kernel receptive field to enhance its edge feature extraction ability. The results of five kinds of ZigBee devices show that the proposed algorithm has higher accuracy than other methods in the case of small sample set. |
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