Individual Recognition Algorithm of IFF Radiation Sources Based on Ensemble Intrinsic Time-scale Decomposition
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摘要:
为研究敌我识别(IFF)辐射源信号的细微特征，针对目前在复杂噪声环境中IFF辐射源个体识别研究不足的问题，该文提出一种基于集成固有时间尺度分解的IFF辐射源个体识别算法。该算法应用集成固有时间尺度分解(EITD)将采样信号自适应划分为若干有实际意义的信号分量并求取IFF辐射源信号在时频域的能量分布图。通过对时频能量谱的纹理分析，以图像的纹理特征表征辐射源信号的无意调制特征，送入支持向量机(SVM)中进行分类识别。实验表明，所提算法相较于基于希尔伯特-黄变换(HHT)、基于固有时间尺度分解(ITD)的辐射源个体识别方法在识别准确度上有较大提升。
Abstract:In order to study the subtle feature recognition of Identification Foe or Friend (IFF) radiation source signals, this paper proposes an IFF individual recognition method based on ensemble intrinsic time-scale decomposition to solve the problem of insufficient research on individual identification of IFF radiation source in complex noise environment. In this algorithm, the Ensemble Intrinsic Time-scale Decomposition (EITD) is applied to dividing the sampled signals into several practical signal components and obtaining the energy distribution diagram of the IFF radiation source signals in time-frequency domain. Through the texture analysis of time-frequency energy spectrum, the unintentional modulation feature of the radiation source signals is represented by the texture features of the image, which are sent to the Support Vector Machine (SVM) for classification and recognition. Experiments show that the proposed method is more accurate than the Hilbert-Huang Transform (HHT) and Inherent Time scale Decomposition (ITD) based method.
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