李维刚, 张鹏, 李孟委,等.基于卡尔曼滤波的主子惯组匹配标定方法设计[J].河南理工大学学报（自然科学版）,2021,40(2):118-126.

LI W G, ZHANG P, LI M W, et al.Design of calibration method for matching of main and sub-inertial groupsbased on Kalman filtering[J].Journal of Henan Polytechnic University(Natural Science) ,2021,40(2):118-126.

基于卡尔曼滤波的主子惯组匹配标定方法设计

李维刚1, 张鹏1, 李孟委1,2, 王树森1

1.中北大学 南通智能光机电研究院，江苏 南通 226000;2.中北大学 电子测试技术国家重点实验室，山西 太原 030051

摘要:针对惯性器件各项误差参数随工作时间发生不确定漂移，影响导航精度，而传统分立式标定方法过度依赖转台性能与测试环境，系统级标定方法存在误差参数滤波收敛速度慢、标定时间过长甚至滤波器发散等问题，本文在低精度转台上外接高精度惯组信息源，利用卡尔曼滤波实现主子惯组匹配标定，同时针对主子惯组匹配标定方法中卡尔曼滤波器构建与传感器布控方法进行研究。结果表明，在把速度误差和姿态误差作为卡尔曼滤波器观测量时，系统状态量在较短时间内能得到良好收敛，IMU误差参数能够得到准确估计。将该方法标定补偿结果与低精度转台传统分立式标定补偿结果进行对照实验，结果证明，该方法能使低精度转台的标定精度得到明显提升，补偿后惯组性能得到有效恢复。

关键词:主子惯组;误差模型;系统级标定;卡尔曼滤波

doi:10.16186/j.cnki.1673-9787.2020030039

基金项目:兵器工业联合基金资助项目（6141B01297）

收稿日期:2020/03/12

修回日期:2020/05/25

出版日期:2021/03/15

Design of calibration method for matching of main and sub-inertial groupsbased on Kalman filtering

LI Weigang1, ZHANG Peng1, LI Mengwei1,2, WANG Shusen1

1.Nantong Institute of Intelligent Opto-mechatronics， North University of China ， Nantong  226000 ， Jiangsu， China;2.Science and Technology on Electronic Test & Measurement Laboratory， North University of China ， Taiyuan  030051 ， Shanxi， China

Abstract:Various error parameters of inertial devices will have uncertain drift with working time and affect navigation accuracy. The traditional discrete calibration method relies too much on the performance of the turntable and the test environment. The system-level calibration method has error parameters， slow convergence rate of filtering， long calibration time， and even filtering issues such as device divergence. It was proposed to connect a high-precision inertial group information source on a low-precision turntable， to use Kalman filtering to achieve the main and sub-inertial group matching calibration， and to study the construction of the Kalman filter and the sensor control method in the main and sub-inertial group matching calibration method. The results showed that when the velocity error and attitude error were used as the Kalman filter observation， the system state quantity could be well converged in a short time， and the IMU error parameter could be accurately estimated The comparison between the calibration compensation results of this method and the traditional discrete calibration compensation results of the low-precision turntable was carried out. The results proved that this method could significantly improve the calibration accuracy of the low-precision turntable， and the performance of the inertial group could be effectively restored after compensation.

Key words:main and sub-inertial group;error model;system-level calibration;Kalman filtering

 基于卡尔曼滤波的主子惯组匹配标定方法设计_李维刚.pdf