由TMS320C32芯片实现陀螺仪漂移卡尔曼滤波算法研究

Implementation of Kalman filtering for gyro drift with TMS320C32 chip

陀螺仪漂移数据经过处理后将是一组高度相关的平稳随机时间序列。在对陀螺仪漂移数据建立时间序列AR模型的基础上,考虑到精度与实时性的要求,采用卡尔曼滤波算法对捷联陀螺"模拟漂移"数据进行了处理,并运用基于TI公司的TMS320C32型DSP对算法进行了实验。通过实时考察实验系统算法程序的运行情况可以看出,卡尔曼滤波算法能有效地提高陀螺精度,并且对于实时性要求高而计算量大的卡尔曼滤波算法,应用DSP技术实现具有良好的发展前景。

Gyro drift data is a high correlative random time sequence by doing some data algorithm. Considered the precision and the realtime, based on building a time sequence AR model for sim-gyro drift data, the SINS sim-gyro drift data is processed using Kalman filter algorithm, and this algorithm is proved by taking a experiment with a TMS320C32 DSP of TI corp. The results show that the Kalman filter algorithm can effectively impove the precision of the gyros, and using DSP to achieve the Kalman filter algorithm is promising.