基于人工神经网络的Loran-C的ASF季节校正

Proceedings of the IEEE 2009 National Aerospace & Electronics Conference (NAECON) Pub Date : 2009-07-21 DOI:10.1109/NAECON.2009.5426607

B. Meng, Xiao-li Xi, Jie Li

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引用次数: 2

摘要

本文利用神经网络减小Loran-C的附加二次相位因子(ASF)误差，以提高导航精度。通过训练，得到了ASF改正量与季节的关系，为补偿Loran-C波的实测时差(TD)提供了依据。结果表明，该方法是有效的，为ASF校正提供了一种新的途径。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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ASF seasonal correction of Loran-C based on artificial neural network

In this paper, neural networks are used to decrease the Additional Secondary Phase Factors (ASF) error of Loran-C to improve the navigation accuracy. Through the training, the relationship between ASF corrections and seasons can be obtained, which is useful to compensate for the measured time-difference(TD) of Loran-C wave. The result proves that this method is effective and provides a new way for ASF correction.

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Proceedings of the IEEE 2009 National Aerospace & Electronics Conference (NAECON)

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