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Study of Ant Colony Algorithm based on adaptive signal processing

机译:基于自适应信号处理的蚁群算法研究

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The paper researches Ant Colony Algorithm (ACA) for anti-jam based on adaptive signal processing. The traditional adaptive processing algorithms usually obtain the partial optimum solution, but paper proposes ant colony algorithm (ACA) can find the desired solution which is a global search method. According to the theory of adaptive signal processing and minimal mean square error (MMSE) criterion, we find the objective function of ACA and found its mathematical model. We define the space of weight vector and deduce the step of ACA in detail in order to compute multidimensional weight vector of element of array antenna. The simulation results show ACA is adapt to adaptive anti-jam technology and can effectively suppress the multi-jam. By comparing with other algorithms, ACA shows the better performance of suppressing interference and protecting desired signal.
机译:本文研究了基于自适应信号处理的蚁群算法(ACA)。传统的自适应处理算法通常会获得部分最优解,但是本文提出了一种蚁群算法(ACA)可以找到理想的解,这是一种全局搜索方法。根据自适应信号处理理论和最小均方误差(MMSE)准则,我们找到了ACA的目标函数并建立了其数学模型。为了计算阵列天线单元的多维权重向量,我们定义了权重向量的空间并详细推导了ACA的步骤。仿真结果表明,ACA适用于自适应抗干扰技术,可以有效抑制多干扰。与其他算法相比,ACA具有更好的抑制干扰和保护所需信号的性能。

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