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An improved star identification method based on neural network

机译:一种改进的基于神经网络的恒星识别方法

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In order to increase the star identification speed and recognition rate of star sensor, an improved rapid star identification method based on neural network (NN) is presented. The proposed method is composed of three levels, including the coarse classification of navigation stars, star pattern recognition based on NN and the final validation of recognition results. The angular distance of characteristic triangle is employed for coarse classification to active the subnets for star pattern recognition. Then the star pattern obtained by the grid method for the main star is sent to the corresponding subnets for the star pattern identification. At last, the identification results of the active subnets are validated to obtain the only recognition result. The experimental results show that, compared with traditional triangle identification method, the proposed method has higher accurate recognition rate, lower redundancy and better robustness.
机译:为了提高恒星传感器的恒星识别速度和识别率,提出了一种改进的基于神经网络的恒星快速识别方法。该方法包括导航星的粗分类,基于神经网络的星型识别和识别结果的最终验证三个层次。特征三角形的角距离用于粗略分类,以激活子网以进行星型识别。然后,将通过网格方法获得的主星的星型发送到相应的子网以进行星型识别。最后,对活动子网的识别结果进行验证,以获得唯一的识别结果。实验结果表明,与传统的三角形识别方法相比,该方法具有较高的识别率,较低的冗余度和较好的鲁棒性。

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