基于混合特征和LVQ神经网络的星识别方法

2018 10th International Conference on Modelling, Identification and Control (ICMIC) Pub Date : 2018-07-01 DOI:10.1109/ICMIC.2018.8529903

Sun Hongchi, Mu Rongjun, Du Huajun

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引用次数: 1

摘要

恒星识别方法是天体导航的基础。为了解决传统方法不能适应高噪声条件的问题，提出了一种基于LVQ神经网络的星识别方法。对比几种不同的特征向量，选择混合特征向量对网络进行训练。仿真结果表明，该方法的识别率为100%，在高噪声条件下的识别率优于传统的恒星识别方法。

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A Star Identification Method Based on Mixed Characteristics and LVQ Neural Network

Star identification method is the basis of celestial navigation. In order to solve the problem that traditional methods can't adapt to high noise condition, a star identification method bases on LVQ neural network is used for star recognition. Compared with several different characteristics vector, the mixed characteristic vector is selected to train the network. The simulation results show that the recognition rate of this star identification method is 100%, and the recognition rate is better than traditional star identification method in high noise condition.

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来源期刊

2018 10th International Conference on Modelling, Identification and Control (ICMIC)

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