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惯导系统对高精度光纤陀螺的输出随机噪声水平要求很高,尤其是角度随机游走将直接影响惯性导航系统的精度。为能有效降低光纤陀螺角度随机游走噪声,分析角度随机游走产生的机理,提出了基于NLMS算法的前向线性预测滤波器(FLP)的降噪方法,该方法比标准LMS算法有更快的收敛速度和良好的动态跟踪特性。用A llan方差法对真实数据滤波前后的噪声水平进行分析比较,结果证明该方法使得光纤陀螺的性能得到了明显的提高,而且该算法简单,工程上易实现,能够有效的提高陀螺的信噪比和惯导系统的对准精度。
The inertial navigation system has high requirements on the output random noise level of the high-precision fiber optic gyroscope. Especially, the random walk of the angle will directly affect the accuracy of the inertial navigation system. In order to effectively reduce the random walk noise of FOG and to analyze the mechanism of random walk, a novel NLP noise reduction method based on NLMS algorithm is proposed, which is faster than the standard LMS algorithm The convergence speed and good dynamic tracking characteristics. A llan variance method is used to analyze and compare the noise level before and after real data filtering. The results show that this method can improve the performance of fiber optic gyroscope. And the algorithm is simple and easy to implement in engineering. It can effectively improve the signal noise of gyroscope Alignment and inertial navigation system than the accuracy.