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Frequency hopping radar signals blind separation using tensor analysis in time domain

机译:跳频雷达在时域中使用张量分析表示盲分离

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Recently, it is very significant task to solve the problem of frequency hopping (FH) signals in the complicated Electromagnetic environment (EME) without prior information. There are many existing methods used to solve this problem but most of them need more computation as result of sparse information and used time-frequency analysis. In this paper, an algorithm based on blind signal separation (BSS) techniques to solve the problem of FH radar signals, the difficulty and the calculations of time-frequency domain are solved by tensor decomposition. Where, the proposed algorithm, exploits tensor decomposition to deal with the blind separation problem of FH radar signals. Also this algorithm can solve the problem without using any sparseness information. The efficiency of the proposed work is tested by Signal to Interference Ratio (SIR) and Mean-Square Error (MSE), as shown in the simulated results.
机译:最近,在没有先前信息的情况下解决复杂电磁环境(EME)中的跳频(FH)信号问题是非常重要的。有许多用于解决这个问题的现有方法,但大多数都需要更多的计算,因为稀疏信息和使用时频分析。本文通过张量分解解决了基于盲信号分离(BSS)技术的基于盲信号分离(BSS)技术来解决FH雷达信号问题的算法,难度和时频域的算法。在其中,所提出的算法,利用张量分解来处理FH雷达信号的盲分离问题。此算法还可以在不使用任何稀疏信息的情况下解决问题。所提出的工作的效率通过信号与干扰比(SIR)和平均误差(MSE)进行测试,如模拟结果所示。

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