基于LSTM网络的空中目标机动识别研究

Fan HanYang, Fan Hongming, Gao Ruiyuan
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引用次数: 3

摘要

针对现有空中目标机动识别算法识别率低、抗噪声性能差的现状,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航迹进行一系列预处理,包括去异常值和插值,重建航迹。经过训练和识别,得到待测目标的机动类型识别结果。通过与HMM模型算法的比较,在相同的训练样本和测试集下,本文设计的算法具有更高的识别率和更好的抗噪性能。
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Research on Air Target Maneuver Recognition Based on LSTM Network
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.
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