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作 者:张孟 彭冲冲 冉营丽 ZHANG Meng;PENG Chong-chong;RAN Ying-li(Zhengzhou University of Industrial Technology,Zhengzhou 451100,China)
出 处:《激光与红外》2025年第1期46-51,共6页Laser & Infrared
基 金:河南省软科学研究项目(No.222400410149)资助。
摘 要:当前方法多采用单一传感温度参数完成补偿,没有对各个传感器的不同温度参数进行区分,导致补偿效果差。对此,提出了一种改进径向基函数的激光陀螺温度漂移补偿方法。首先,采用小波分解含有噪声的激光陀螺漂移信号,求出并校正每个尺度的小波系数,得到重构后无干扰温度传感信号;然后,通过脉冲矢量、装配误差矩阵等数值,测量激光陀螺加速计,分辨出各传感器的温度参数。利用自组织特征映射网络分类激光陀螺输出参数,选择径向基函数神经网络转换函数,算出每个温度传感器参数的误差减少率。最后,结合正交最小二乘算法训练径向基函数神经网络,完成激光陀螺温度漂移补偿。通过实验,证明所提方法激光陀螺温度漂移补偿效果佳,输出稳定性,可增强高精度的导航、定位、定向等设备性能。The current method mostly adopts a single sensing temperature parameter for compensation,without distinguishing the different temperature parameters of each sensor,resulting in a poor compensation effect.In this regard,a temperature drift compensation method for laser gyroscopes with improved radial basis functions is proposed.Firstly,wavelet decomposition is used to decompose the drift signal of the laser gyroscope containing noise,and the wavelet coefficients of each scale are calculated and corrected to obtain the reconstructed non-interference temperature sensing signal.Then,by using values such as pulse vector and assembly error matrix,the laser gyroscope accelerometer is measured to distinguish the temperature parameters of each sensor.The self-organized feature mapping network is used to classify the laser gyro output parameters,and the radial basis function neural network transformation function is selected to calculate the error reduction rate of each temperature sensor parameter.Finally,the radial basis function neural network is trained with the orthogonal least squares algorithm to complete the temperature drift compensation of the laser gyroscope.Through experiments,it is proved that the proposed method for temperature drift compensation of laser gyroscopes has good performance,stable output,and can enhance the performance of high-precision navigation,positioning,orientation and other equipment.
分 类 号:TN249[电子电信—物理电子学] TM935[电气工程—电力电子与电力传动]
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