摘要
Introduces the principle of strap-down north-finder and studies the question of improving the precision of north-finder when under a random disturbance. Neural network has the ability of simulating non-linear curves. It can thus simulate the output of the north-finder. The paper shows a design for a hybrid filter that combines neural network and low-pass filter. When the north-finder meets with a random disturbance, the output of neural network will replace the output of the north-finder. The result of filtering the real-data that has random distrubance shows that this hybrid filter can reduce the influence of random disturbance efficiently.
| 源语言 | 英语 |
|---|---|
| 页（从-至） | 330-333 |
| 页数 | 4 |
| 期刊 | Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology |
| 卷 | 21 |
| 期 | 3 |
| 出版状态 | 已出版 - 2001 |
指纹
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Zhang, Y. F., Chen, J. B., Zhu, C. Z., Zhang, L., & Wang, X. R. (2001). A neural network hybrid filter used in strap-down north-finder. Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology, 21(3), 330-333.