A neural network hybrid filter used in strap-down north-finder

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.