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Research on Air Target Maneuver Recognition Based on LSTM Network

机译:基于LSTM网络的空中目标机动识别研究

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Aiming at the current fact of low recognition rate and poor anti-noise performance of the existing air target maneuver recognition algorithms, a method of target maneuver recognition based on LSTM network was studied. Input of the LSTM network is getting by a series of preprocessing on the original track, including eliminating outliers and interpolation, and reconstructing the track. After training and recognition, the maneuver type recognition result of the target to be measured is obtained. By comparing with HMM model algorithm, the algorithm designed in this paper turns out to be of higher recognition rate and better anti-noise performance under the same training sample and test set.
机译:针对目前空中目标机动识别算法识别率低,抗噪性能差的现状,研究了一种基于LSTM网络的目标机动识别方法。 LSTM网络的输入是通过对原始轨道进行一系列预处理而获得的,包括消除离群值和内插以及重构轨道。经过训练和识别,获得待测目标的机动类型识别结果。与HMM模型算法相比,本文设计的算法在相同训练样本和测试集下具有较高的识别率和较好的抗噪性能。

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