灰色卡尔曼滤波的主瓣移动干扰抑制方法

Movingmainlobe jamming suppression method based on Gray Model Kalman Filter

  • 摘要: 现有的基于和差通道的主瓣干扰对消技术中对消通道间的比例系数多采用维纳滤波的方法进行估计,然而维纳滤波仅适用于平稳随机信号的估计,即该方法仅在干扰源静止的条件下有效,但是当干扰源处于移动过程中时,干扰信号为非平稳随机信号,此时维纳滤波的方法便失去作用。为此,本文提出了一种基于灰色卡尔曼滤波的主瓣移动干扰抑制方法。该方法采用基于灰色模型的卡尔曼滤波器对相消通道间的比例系数进行预测,能够有效地消除移动干扰源所产生的主瓣干扰。

     

    Abstract: The proportional coefficient estimation of channel cancellation technology in the existing mainlobe jamming suppression method which based on sum and difference beamforming normally use Wiener filtering. However,the Wiener filtering only apply to stationary stochastic signal while jamming is static. It is failure in nonstationary stochastic signal while jamming is moving. Therefore,we present the moving mainlobe jamming suppression method based on Gray Model Kalman Filter. Which can predict the proportional coefficient of channel cancellation and emit moving mainlobe jamming effectively.

     

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