基于DSP的球碟转子式陀螺仪信号处理技术研究

发布时间：2018-02-24 21:27

本文关键词： 陀螺信号降噪 DSP硬件设计经典滤波算法卡尔曼滤波算法　出处：《哈尔滨工业大学》2015年硕士论文　论文类型：学位论文

【摘要】：在陀螺仪工作过程中,陀螺仪中的随机噪声会大大影响陀螺仪的性能。本文针对哈尔滨工业大学提出的新型结构陀螺仪应用经典滤波算法和现代滤波算法,有效的减小了陀螺仪信号中的随机噪声。提高陀螺系统的性能主要从陀螺仪结构优化和陀螺仪信号后处理两个方面考虑。本文针对哈尔滨工业大学MEMS中心提出的新型结构陀螺仪(球碟转子式陀螺仪)进行信号后处理研究。新型的球碟转子式陀螺结构相比于已有的陀螺结构是一种全新的结构,所以以前的信号后处理方式可能不适用。本文针对这一新型结构进行经典滤波和现代滤波的应用研究,以提高陀螺整体性能。首先,本文对滤波算法运行的硬件平台进行设计,其中以TMS320F2812作为主要的运算和控制单元,以采样芯片AD7655作为陀螺信号采集芯片,并在此基础上加入了DA模块和DDS模块,方便陀螺后续的载波输出和伺服研究。根据硬件设计,本文编写了各个模块的驱动程序。最终实验测量表明,AD采样精度可以达到14位,采样速率可以达到200k Hz。其次,在完成了硬件平台的设计后,本文应用MATLAB滤波器设计工具箱设计IIR滤波算法,然后导入Simulink进行仿真验证。之后在DSP平台上编写算法,并对滤波算法进行了优化处理,在硬件平台的实验表明,DSP能够实时滤除80%以上的不在有用频段的噪声信号。再次,经典滤波算法从频率角度出发,虽然能够滤除和信号不在同一频段的大部分噪声,但是对于和信号在同一频段的噪声却无能为力。本文针对这一问题应用了卡尔曼滤波算法。卡尔曼滤波算法要求被处理信号中的噪声为白噪声并且有准确的数学模型,因此本文对采集到的陀螺信号进行了预处理,得到陀螺信号的轮次值为96,峰度值为3.0149,偏度值为0.0474,满足平稳正态分布。然后建立了陀螺信号的ARMA模型。通过卡尔曼滤波算法,将随机信号方差由3.0041×10-7减小到7.3704×10-8,有效的滤除了信号中的随机噪声,对于提高陀螺偏置稳定性有很大帮助。
[Abstract]:In the working process of gyroscopes, random noise in gyroscopes will greatly affect the performance of gyroscopes. In this paper, classical filtering algorithms and modern filtering algorithms are applied to the novel structural gyroscopes proposed by Harbin University of Technology. It can effectively reduce the random noise in the gyroscope signal. Improving the performance of gyroscope system is mainly considered from two aspects: the optimization of gyroscope structure and the post-processing of gyroscope signal. This paper aims at the MEMS Center of Harbin University of Technology. The new structure gyroscope (spherical disk rotor gyroscope) is a new structure compared with the existing gyroscope. In order to improve the overall performance of gyroscope, this paper designs the hardware platform of filtering algorithm, which is based on the application of classical filtering and modern filtering, in order to improve the overall performance of gyroscope. TMS320F2812 is used as the main operation and control unit, and the sampling chip AD7655 is used as the gyro signal acquisition chip. On this basis, DA module and DDS module are added to facilitate the research of the subsequent carrier output and servo of gyroscope. The driver program of each module is written in this paper. The final experimental measurement shows that the sampling precision of AD can reach 14 bits and the sampling rate can reach 200kHz. Secondly, after the hardware platform is designed, In this paper, IIR filter algorithm is designed with MATLAB filter design toolbox, then imported into Simulink for simulation verification. Then the algorithm is written on DSP platform, and the filter algorithm is optimized. Experiments on the hardware platform show that the DSP can filter more than 80% noise signals which are not in the useful frequency band in real time. Thirdly, the classical filtering algorithm can filter most of the noise which is not in the same frequency band as the signal although the classical filtering algorithm can filter the noise from the frequency point of view. However, there is no way to deal with the noise in the same frequency band as the signal. In this paper, the Kalman filter algorithm is applied to this problem. The Kalman filtering algorithm requires the noise in the processed signal to be white noise and has an accurate mathematical model. Therefore, the gyro signal is preprocessed in this paper, and the gyro signal is obtained with a rotation value of 96, a kurtosis value of 3.0149 and a bias value of 0.0474.Then, the ARMA model of the gyro signal is established, and the Kalman filter algorithm is used. The variance of random signal is reduced from 3.0041 脳 10 ~ (-7) to 7.3704 脳 10 ~ (-8), which can effectively filter the random noise in the signal and improve the bias stability of gyroscope.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TN96;TN911.7

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