Abstract
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.
Original language | English |
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Pages (from-to) | 330-333 |
Number of pages | 4 |
Journal | Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology |
Volume | 21 |
Issue number | 3 |
Publication status | Published - 2001 |
Keywords
- Integrated filter
- Neural network
- North-finder