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Method of Forming Classified Training Sample in Case of Spacial Signal Processing under Influence of Combined Interference

机译:联合干扰影响下空间信号处理中分类训练样本的形成方法

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摘要

Under the conditions of the combined interference, the operation efficiency of the radar equipment is substantially deteriorated. This is due to the decorrelation of the signals of the point source of active interference acting on the radar by passive interference. In this article methods of formation of the classified training sample, generated only by active interference, are considered for adaptation of the weight coefficients of spatial filters under conditions of combined interference presence. An effective method of forming the classified training sample generated by active masking interference was developed for spatial processing of radar signals under conditions of simultaneous exposure to passive interference. The developed method of forming the training sample is based on estimating the width of the normalized autocorrelation function in each element of the distance resolution. The current analysis of the combined interference components in each resolution element improves the quality of the interference component classification and, as a result, minimizes the effect of passive interference on the adaptation process of the spatial filter. The theoretical and practical aspects of the formation of the classified training sample are considered. The functional scheme of the classifier for the combined interference components is developed. The efficiency of the proposed method is compared with known correlation methods. The current analysis of the combined interference components in each element of the range resolution improves the quality of interference classification, which is important in the context of complex hydrometeorological conditions.
机译:在合并干扰的条件下,雷达设备的运行效率大大降低。这是由于无源干扰作用在雷达上的有源干扰点源信号的去相关。在本文中,考虑了仅由主动干扰生成的分类训练样本的形成方法,用于在存在干扰的条件下适应空间滤波器的权重系数。针对在同时暴露于无源干扰的条件下对雷达信号进行空间处理,开发了一种有效的形成由有源掩蔽干扰产生的分类训练样本的方法。形成训练样本的开发方法是基于估计距离分辨率的每个元素中归一化自相关函数的宽度。当前对每个分辨率元素中组合干扰分量的分析提高了干扰分量分类的质量,因此,将无源干扰对空间滤波器适应过程的影响降至最低。考虑了分类训练样本的形成的理论和实践方面。提出了组合干扰分量分类器的功能方案。将该方法的效率与已知的相关方法进行了比较。当前对距离分辨率每个要素中组合干扰分量的分析提高了干扰分类的质量,这在复杂的水文气象条件下非常重要。

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