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Feature Extraction and Recognition of Aerial Objects using Echo Signals Received by Radar

机译:雷达接收的回波信号的特征提取与空中物体的识别

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The article describes methods for extracting valuable data from echo signals received from natural and artificial aerial objects recognized by mobile radar stations. Options for filtering the signal reflected from air objects, presented in a complex form, are considered. A method for identifying signal features based on radial basis functions is developed. A hybrid model of the classifier for the recognition of unmanned aerial vehicles and ornithological objects is proposed. It includes subsystems for filtering, feature detection based on clustering and approximation functions, as well as the classifier itself. Methods of recognition based on neural networks are considered. To train the classifier was used a library based on the principle of gradient boosting of decision trees. An experimental sample was used to train and test the classifier.
机译:该物品介绍从由移动雷达站识别的自然和人工空穴物体接收的回波信号中提取有价值数据的方法。 考虑了过滤从空气对象反射的信号,以复杂形式呈现的信号。 开发了一种用于识别基于径向基函数的信号特征的方法。 提出了一种用于识别无人空中车辆和鸟类物体的分类器的混合模型。 它包括用于过滤的子系统,基于聚类和近似函数以及分类器本身的特征检测。 考虑了基于神经网络的识别方法。 为了训练分类器是基于决策树渐变升压原理的图书馆。 使用实验样品培训和测试分类器。

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