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为了有效抑制机抖激光陀螺(RLG)输出数据中的随机漂移,提出了采用新陈代谢GM(1,1)灰色模型与时间序列模型融合的灰色时序建模新方法。依据所建模型对激光陀螺的漂移数据进行Kalman滤波,并利用Allan方差法对建模滤波前后的陀螺数据进行分析对比。结果表明:该方法抑制激光陀螺随机漂移的效果优于传统的时序建模后Kalman滤波的方法,有效降低了激光陀螺的量化误差、角度随机游走、零偏不稳定性、角速率随机游走、速率斜坡;相对于传统方法,对量化误差的改善尤为明显。
In order to effectively suppress the random drift in the output data of RLG, a new gray time series modeling method based on the fusion of GM (1,1) gray model and time series model is proposed. Based on the model, the Kalman filter of the laser gyro drift data is carried out, and the Allan variance method is used to analyze and compare the gyro data before and after modeling filtering. The results show that the proposed method is superior to traditional Kalman filtering in time series modeling to reduce the random drift of the laser gyro, which can effectively reduce the quantization error, random walk, angular instability and random walk of the laser gyro , The rate of slope; Compared with the traditional method, the improvement of quantization error is especially obvious.