Performance analysis of IMU fine alignment based on wavelet de-noising
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摘要: 精对准性能是保障惯性导航精度必不可少的重要条件,论文总结了国内外精对准的研究现状,发现精对准一般是通过卡尔曼滤波和惯性传感器的小失准角线性误差方程实现;基于此,本文通过卡尔曼滤波及小波分析,对低、中、高三种不同性能的惯性传感器进行精对准性能分析,对比发现,高精度的惯性传感器有着较好的对准精度;而低精度的传感器,由于噪声偏差及非线性原因,对准精度较低,甚至出现滤波发散的情况.Abstract: Precision alignment performance is an essential condition to ensure the accuracy of inertial navigation. This paper summarizes the research status of precision alignment at home and abroad, and finds that precision alignment is usually achieved by Kalman filter and linear error equation of small misalignment angle of inertial sensor. Based on this, Kalman filter and wavelet analysis are used in this paper. The precision alignment performance of three kinds of inertial sensors with different performances is analyzed. It is found that the high precision inertial sensors have better alignment accuracy, while the low precision sensors have lower alignment accuracy due to noise deviation and non-linear reasons, even the situation of filter divergence.
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Key words:
- strapdown inertial navigation system /
- wavelet analysis /
- de-noising /
- fine alignment /
- Kalman filter
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