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Target recognition from SAR data using range profiles and a long short-term memory (LSTM) network

机译:利用距离像和长短时记忆(LSTM)网络从SAR数据中识别目标

摘要

A method of identifying a target from synthetic aperture radar (SAR) data without incurring the computational load associated with generating an SAR image. The method includes receiving SAR data collected by a radar system including RF phase history data associated with reflected RF pulses from a target in a scene, but excluding an SAR image. Range profile data is determined from the SAR data by converting the RF phase history data into a structured temporal array that can be applied as input to a classifier incorporating a recurrent neural network, such as a recurrent neural network made up of long short-term memory (LSTM) cells that are configured to recognize temporal or spatial characteristics associated with a target, and provide an identification of a target based on the recognized temporal or spatial characteristic.
机译:一种从合成孔径雷达(SAR)数据中识别目标的方法,无需产生与生成SAR图像相关的计算负载。该方法包括接收由雷达系统收集的SAR数据,该数据包括与来自场景中目标的反射RF脉冲相关联的RF相位历史数据,但不包括SAR图像。通过将射频相位历史数据转换为结构化时间阵列,从SAR数据确定距离剖面数据,该结构化时间阵列可作为输入应用于包含递归神经网络的分类器,例如由长短时记忆(LSTM)单元组成的递归神经网络,该单元被配置为识别与目标相关的时间或空间特征,以及基于所识别的时间或空间特征提供目标的识别。

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