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Methods of Forming Classified Training Sample for Adaptation of Weight Coefficient of Automatic Interference Compensator

机译:自动干扰补偿器权重适应的分类训练样本形成方法

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摘要

Abstract The problem of analyzing various methods for the formation of the classified training sample that ensure the effective operation of the automatic compensator for active interferences with simultaneous presence of passive interference is solved in this paper. For the first time an adaptive method for the formation of the classified training sample based on the use of threshold estimation of the interchannel correlation coefficient of the combined interference is proposed. An adaptive method for the formation of the classified training sample based on the current interval estimation of the distribution of the passive component of the combined interference in range (time) is also proposed. The method provides an estimation of the coefficient of interchannel correlation with the selection of the maximum value and its utilization for the formation of weight coefficients in the following probing period. Experiment in the testing ground is conducted with a quantitative estimation of the cancellation ratio of active interference for the formation of the classification sample using spectral differences in the structure of active and passive interferences.
机译:摘要本文解决了分析分类训练样本的各种方法的问题,以确保自动补偿器有效地处理有源干扰并同时存在无源干扰。首次提出了一种自适应方法,用于基于组合干扰的信道间相关系数的阈值估计的使用来形成分类训练样本。还提出了一种自适应方法,该方法用于基于范围(时间)中组合干扰的无源分量分布的当前间隔估计来形成分类训练样本。该方法提供了信道间相关系数的估计以及最大值的选择及其在随后的探测周期中的权重系数的形成。使用有源和无源干扰的结构中的光谱差异,在测试场上进行实验,对有源干扰的消除比率进行定量估计,以形成分类样本。

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