摘要
介绍捷联式寻北仪的工作原理 ,研究当车体受到随机干扰时如何提高寻北仪的寻北精度问题。神经网络对非线性曲线具有较好的曲线拟合能力 ,用神经网络模拟寻北仪输出信号 ,用神经网络和低通滤波器相结合的组合滤波器对寻北仪输出数据进行处理 ,当系统受到冲击干扰时 ,用神经网络的输出代替实际传感器的输出。通过对实际的带有干扰的信号滤波结果表明 ,该组合滤波器能较好地抑制随机干扰对寻北结果的影响。
Introduces the principle of strap down north finder and studies the question of improving the precision of north finder when under a random distur bance. 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.
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2001年第3期330-333,共4页
Transactions of Beijing Institute of Technology
基金
部级预研项目
