基于改进Fuzzy ART的自适应雷达信号分选

Adaptive Radar Signal Sorting Based on Improved Fuzzy ART

  • 摘要: 侦察接收机对获取的辐射源波形去交织以分离不同信号,称为信号分选,是电磁频谱战系统的核心技术.复杂电磁环境下脉冲流密度大、时域波形及诸域特征严重交叠,导致多数基于无监督模型的信号分选方法难以胜任.提出一种可自适应调整警戒阈值的模糊自适应共振理论(AVT fuzzy ART)聚类算法,基于对属性差异敏感的曼哈顿距离自适应调整警戒阈值,依据在线累积数据得出的辐射源瞬态聚类概率对警戒阈值动态加权.仿真结果表明,该方法能在无历史先验信息的条件下胜任多类别辐射源信号去交错.

     

    Abstract: Being able to remove the interweavement in waveforms came from radiation sources for signal separation, signal sorting can be used as a core technology in electromagnetic spectrum warfare systems of reconnaissance receivers. In order to solve the problems about the high density of pulse streams and severe overlapping of temporal waveforms with domain characteristics in complex electromagnetic environments, an Adaptive Vigilance Threshold Fuzzy Adaptive Resonance Theory (AVT Fuzzy ART) clustering algorithm was proposed to adjust the vigilance threshold adaptively based on the Manhattan distance sensitized to attribute differences, solving the algorithm inadequate problems for most unsupervised model-based signal sorting algorithms. And the proposed algorithm was also designed to weight dynamically for the vigilance threshold based on the transient clustering probability of radiation sources derived from online accumulated data. Simulation results show that the algorithm is competent to eliminate the interweavement of multi-category radiation source signals without prior historical information.

     

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