船用光纤捷联惯导系统标定与海上对准技术研究
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摘要
随着光纤陀螺精度的提高,船用光纤陀螺捷联惯性导航系统正处于产品开发阶段。船用光纤陀螺捷联惯性导航系统涉及的关键技术包括很多方面,主要集中在标定技术、初始对准技术、综合校准技术、阻尼技术等几方面。本文从提高船用光纤陀螺捷联惯导系统的实际需求出发,对系统标定技术和海上对准技术展开研究。主要工作有：
首先,对光纤陀螺组件和加速度计组件进行误差建模,建立标定误差与载体角速率和比力之间的关系,推导标定误差对捷联惯性导航系统导航误差的影响,并对其进行分析,研究标定误差对捷联惯性导航系统摇摆运动和匀加速直线运动情况下导航误差的影响,对其进行仿真验证。
其次,对分立式标定方法进行误差分析和计算机仿真,分析三轴惯导测试转台速率误差和定位误差对惯性测量单元标定结果的影响。提出了一种光纤陀螺组件六位置分立式标定方法,降低了转台误差对光纤陀螺组件标定结果的影响,消除了光纤陀螺组件标定参数之间的耦合误差。仿真分析和导航实验证明,六位置分立式标定方法提高了光纤陀螺组件的标定精度。
第三,设计了光纤陀螺组件和加速度计组件的闭环标定方案。对闭环标定方法展开研究,将开环标定结果作为闭环标定的初始值,利用三轴惯导测试转台提供的姿态修正光纤陀螺组件的标度因数和安装误差,利用三轴惯导测试转台提供的速度修正加速度计组件的标度因数和安装误差,直到两次标定参数之差小于给定值,闭环标定结束。试验结果表明,闭环标定提高了系统的标定精度。
第四,提出了一种十位置系统级标定方法,将标定误差引入静基座光纤捷联惯导系统速度误差方程和姿态误差方程,利用三轴惯性测试转台提供的速度和姿态,采用Kalman滤波对标定误差进行估计,通过解耦运算实现光纤陀螺组件和加速度计组件标定误差参数的分离,并对其进行仿真和实验验证。利用Kalman滤波器滤波开始一段时间内跟踪速度快的特点,将标定误差分成多次进行估计,并在十位置系统级标定的基础上,设计了光纤陀螺组件多级系统级标定方案,仿真和实验证明多级系统级标定能提高光纤陀螺组件的标定精度。
最后,本文提出了一种基于混合动态滤波的海上大方位失准角对准方法。采用平台误差角表示理论导航坐标系与计算导航坐标系之间的失准角,推导捷联惯导系统误差方程,并对其进行简化,得到满足船用光纤捷联惯导系统海上大方位失准角对准的误差模型。对混合动态滤波模型进行描述,重点介绍EKF-KF和UKF-KF两种混合动态滤波递推公式,给出了线性估计和非线性估计融合的具体方法,将海上对准误差模型中的线性状念和非线性状态进行分离,采用非线性滤波EKF和UKF估计系统的方位失准角,采用线性滤波KF估计系统的水平失准角,并将方位失准角的估计方差作为修正项反馈到水平失准角的估计中以提高估计的精度。仿真证明采用混合动态滤波方法提高了船用光纤陀螺捷联惯导系统海上对准的精度。
With the precision improvement of the fiber optic gyro (FOG), marine FOG strapdown inertial navigation system (SINS) is at the product development stage. The key technologies of marine FOG strapdown inertial navigation system include the calibration technology, initial alignment technology, comprehensive calibration technology, damping technology et al. According to practical requirements of marine FOG strapdown navigation system, this paper mainly focuses on the research of the calibration technology and offshore initial alignment technology, which can be summarized as follows:
Firstly, by establishing the FOG unit error model and the accelerometer unit error model, the relationship between the calibration error, the body angular rate and the acceleration are analyzed. The equation between the calibration error and strapdown inertial navigation system error is derived. The navigation error brought by the calibration error under the swaying motion and uniformly accelerated rectilinear motion is derived and the analysis is confirmed by simulation results.
Secondly, the error analysis of schism calibration method and simulations are performed, which shows the inertial measurement unit (IMU) calibration error brought by the velocity error and orientation error of three-axis turntable. A 6-position discrete calibration method is proposed for FOG unit, which reduces the FOG unit calibration error brought by the three-axis turntable error and eliminats the coupled error among FOG parameters, and finally improves the calibration precision. Simulation and navigation experiments confirm that 6-position discrete calibration method improves the calibration precision.
Thirdly, FOG unit closed-loop calibration method and accelerometer unit closed-loop calibration are performed, in which the result of open-loop calibration is used as initial value of closed-loop calibration. The attitude provided by the three-axis turntable is used to revise the FOG scale factor and installation error, and the velocity provided by the three-axis turntable is used to revise the accelerometer scale factor and installation error. The calculation of the closed-loop calibration will continue until the difference of parameters between two neighboring revision is smaller than a given value. Experimental results show that the closed-loop calibration method can increase the system calibration precision.
Fourthly, a 10-poistion systematic calibration is proposed by using the calibration error in the static velocity error equation and attitude error equation. In this method, Kalman filter is used to estimate the calibration error by utilizing the three-axis turntable's velocity and attitude. One property of Kalman filter is that the tracking speed is quick at the beginning. Based on this property of Kalman filter, a multistage systematic calibration method is designed in this paper. The calibration of multistage systematic calibration is the same as 10-poistion systematic calibration, but it reuses the Kalman filter to estimate the calibration error. Simulation and experiment results show that this multistage systematic calibration method can improve the calibration precision of FOG.
Finally, an offshore initial alignment with large azimuth misalignment method is proposed in this paper, which is based on a mixed dynamic filter algorithm. is applied in the offshore initial alignment with large azimuth misalignment. The misalignment between the theory navigation coordinate frame and the calculated navigation coordinate frame are indicated by Euler platform error angles. Derive the strapdown inertial navigation system error equation under large azimuth misalignment and simplify it to meet the offshore fine initial alignment model of marine fiber optic gyro strapdown inertial navigation system. Describe the mixed dynamic filter model. It described the EKF-KF and UKF-KF in detail and gave the integration of linear estimate and non-linear estimate. Separate the non-linear state from the linear state. The nonlinear filters that are EKF and UKF are used to estimate the nonlinear state which is azimuth misalignment. The linear filters KF is used to estimate the linear state which are horizontal misalignment. The EKF-KF and UKF-KF take the estimate variance of azimuth misalignment as a feed bake to revise the horizontal misalignment estimate. It can improve the estimate precision. The simulation proved the validity of the mixed dynamic filter algorithm.
首先,对光纤陀螺组件和加速度计组件进行误差建模,建立标定误差与载体角速率和比力之间的关系,推导标定误差对捷联惯性导航系统导航误差的影响,并对其进行分析,研究标定误差对捷联惯性导航系统摇摆运动和匀加速直线运动情况下导航误差的影响,对其进行仿真验证。
其次,对分立式标定方法进行误差分析和计算机仿真,分析三轴惯导测试转台速率误差和定位误差对惯性测量单元标定结果的影响。提出了一种光纤陀螺组件六位置分立式标定方法,降低了转台误差对光纤陀螺组件标定结果的影响,消除了光纤陀螺组件标定参数之间的耦合误差。仿真分析和导航实验证明,六位置分立式标定方法提高了光纤陀螺组件的标定精度。
第三,设计了光纤陀螺组件和加速度计组件的闭环标定方案。对闭环标定方法展开研究,将开环标定结果作为闭环标定的初始值,利用三轴惯导测试转台提供的姿态修正光纤陀螺组件的标度因数和安装误差,利用三轴惯导测试转台提供的速度修正加速度计组件的标度因数和安装误差,直到两次标定参数之差小于给定值,闭环标定结束。试验结果表明,闭环标定提高了系统的标定精度。
第四,提出了一种十位置系统级标定方法,将标定误差引入静基座光纤捷联惯导系统速度误差方程和姿态误差方程,利用三轴惯性测试转台提供的速度和姿态,采用Kalman滤波对标定误差进行估计,通过解耦运算实现光纤陀螺组件和加速度计组件标定误差参数的分离,并对其进行仿真和实验验证。利用Kalman滤波器滤波开始一段时间内跟踪速度快的特点,将标定误差分成多次进行估计,并在十位置系统级标定的基础上,设计了光纤陀螺组件多级系统级标定方案,仿真和实验证明多级系统级标定能提高光纤陀螺组件的标定精度。
最后,本文提出了一种基于混合动态滤波的海上大方位失准角对准方法。采用平台误差角表示理论导航坐标系与计算导航坐标系之间的失准角,推导捷联惯导系统误差方程,并对其进行简化,得到满足船用光纤捷联惯导系统海上大方位失准角对准的误差模型。对混合动态滤波模型进行描述,重点介绍EKF-KF和UKF-KF两种混合动态滤波递推公式,给出了线性估计和非线性估计融合的具体方法,将海上对准误差模型中的线性状念和非线性状态进行分离,采用非线性滤波EKF和UKF估计系统的方位失准角,采用线性滤波KF估计系统的水平失准角,并将方位失准角的估计方差作为修正项反馈到水平失准角的估计中以提高估计的精度。仿真证明采用混合动态滤波方法提高了船用光纤陀螺捷联惯导系统海上对准的精度。
With the precision improvement of the fiber optic gyro (FOG), marine FOG strapdown inertial navigation system (SINS) is at the product development stage. The key technologies of marine FOG strapdown inertial navigation system include the calibration technology, initial alignment technology, comprehensive calibration technology, damping technology et al. According to practical requirements of marine FOG strapdown navigation system, this paper mainly focuses on the research of the calibration technology and offshore initial alignment technology, which can be summarized as follows:
Firstly, by establishing the FOG unit error model and the accelerometer unit error model, the relationship between the calibration error, the body angular rate and the acceleration are analyzed. The equation between the calibration error and strapdown inertial navigation system error is derived. The navigation error brought by the calibration error under the swaying motion and uniformly accelerated rectilinear motion is derived and the analysis is confirmed by simulation results.
Secondly, the error analysis of schism calibration method and simulations are performed, which shows the inertial measurement unit (IMU) calibration error brought by the velocity error and orientation error of three-axis turntable. A 6-position discrete calibration method is proposed for FOG unit, which reduces the FOG unit calibration error brought by the three-axis turntable error and eliminats the coupled error among FOG parameters, and finally improves the calibration precision. Simulation and navigation experiments confirm that 6-position discrete calibration method improves the calibration precision.
Thirdly, FOG unit closed-loop calibration method and accelerometer unit closed-loop calibration are performed, in which the result of open-loop calibration is used as initial value of closed-loop calibration. The attitude provided by the three-axis turntable is used to revise the FOG scale factor and installation error, and the velocity provided by the three-axis turntable is used to revise the accelerometer scale factor and installation error. The calculation of the closed-loop calibration will continue until the difference of parameters between two neighboring revision is smaller than a given value. Experimental results show that the closed-loop calibration method can increase the system calibration precision.
Fourthly, a 10-poistion systematic calibration is proposed by using the calibration error in the static velocity error equation and attitude error equation. In this method, Kalman filter is used to estimate the calibration error by utilizing the three-axis turntable's velocity and attitude. One property of Kalman filter is that the tracking speed is quick at the beginning. Based on this property of Kalman filter, a multistage systematic calibration method is designed in this paper. The calibration of multistage systematic calibration is the same as 10-poistion systematic calibration, but it reuses the Kalman filter to estimate the calibration error. Simulation and experiment results show that this multistage systematic calibration method can improve the calibration precision of FOG.
Finally, an offshore initial alignment with large azimuth misalignment method is proposed in this paper, which is based on a mixed dynamic filter algorithm. is applied in the offshore initial alignment with large azimuth misalignment. The misalignment between the theory navigation coordinate frame and the calculated navigation coordinate frame are indicated by Euler platform error angles. Derive the strapdown inertial navigation system error equation under large azimuth misalignment and simplify it to meet the offshore fine initial alignment model of marine fiber optic gyro strapdown inertial navigation system. Describe the mixed dynamic filter model. It described the EKF-KF and UKF-KF in detail and gave the integration of linear estimate and non-linear estimate. Separate the non-linear state from the linear state. The nonlinear filters that are EKF and UKF are used to estimate the nonlinear state which is azimuth misalignment. The linear filters KF is used to estimate the linear state which are horizontal misalignment. The EKF-KF and UKF-KF take the estimate variance of azimuth misalignment as a feed bake to revise the horizontal misalignment estimate. It can improve the estimate precision. The simulation proved the validity of the mixed dynamic filter algorithm.
引文
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