摘要
微惯性测量单元(Micro Inertial Measurement Unit)具有体积小、重量轻、成本低、可靠性高等特点,在军事及民用领域具有广阔的应用前景。陀螺及加速度计是MIMU的主要元件,其精度直接影响到惯性系统的精度。实际工作中,由于不可避免的有各种干扰因素作用导致陀螺及加速度计产生误差。这些误差,一方面是器件本身结构不完善引起的;另一方面,也和其所处的工作环境和工作条件有关。主要围绕MIMU误差补偿进行了以下研究:
分析了微陀螺及加速度计的工作和结构原理,从理论上分析了影响其精度的主要误差来源,并建立了陀螺及加速度计的误差模型,采用“六位置24点”编排对陀螺及加速度计的主要误差及性能进行了标定。
针对MIMU对温度影响敏感的特点,对陀螺及加速度计的温度特性进行了分析,分别采用离线标定和在线辨识的方法确立温度补偿模型参数并用于补偿。实验结果表明,陀螺的零偏稳定性由补偿前的126.324°/h减小到9.612°/h,加速度计的偏置稳定性由补偿前的0.836 mg减小到0.216 mg;为进一步提高补偿效率,引入了Kalman滤波对温度传感器测量值进行滤波处理后再用于补偿,减小了补偿过程中由于温度测量噪声而引入的额外误差,陀螺零偏稳定性由9.612°/h下降到8.964°/h,加速度计偏置稳定性由0.216mg下降到0.176mg。陀螺效果改善不大,这是因为陀螺温度传感器本身的测量噪声很小,而且主要由本身的量测噪声决定;但对温度传感器量测噪声较大的局部而言,其噪声能够减小18%。
对陀螺随机漂移建模进行了研究,运用随机信号处理方法以及时间序列分析法建立了陀螺随机漂移的AR模型,并根据Akaike信息准则中的AIC准则和Kalman滤波对模型的适用性及准确性进行了检验,实验结果验证了该方法的正确性。
Micro Inertial Measurement Unit (MIMU) has many advantages such as small volume, light weight, low cost, high reliability etc. It will be applied broadly in the field of military and civil. Inertial navigation gyroscope and accelerometer are important parts of the inertial system and its precision will directly influence the precision of inertial system. Actually, error in measurement will be caused inevitably due to many disturbing factors. On one hand, the imperfect structure of MIMU will cause error; on the other hand, error may occur due to the working environment and condition of the MIMU. The error compensation about MIMU is studied in this paper. A series of results are presented as follows:
Analyses the main error factors of accelerometer and gyro according to its structural characteristics, the simple mathematic models of micro gyro and accelerometer are established based on the results of velocity and 24 position calibration.
The temperature characteristics of gyroscope and accelerometer have been studied. The temperature compensation models of gyroscope and accelerometer bias have been established. Through compensation, the bias stability of the gyroscope is reduced from 126.324°/h to 9.612°/h and that of accelerometer is reduced from 0.836mg to 0.216mg.The compensation models have been further improved by pre-filtering before compensation. The bias stability is reduced to 8.964°/h and 0.176mg for gyroscope and accelerometer, respectively.
Non-stationary random signal of gyro drift is studied. The AR model of the random signal is established by using stochastic signal processing methods and time series analysis theory. This method is proved by AIC rule and Kalman filter.
引文
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