| 双轴连续旋转调制捷联惯导系统大失准角初始对准技术 |
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| 引用本文： | 许昊天,赵春柳,邵海俊,缪玲娟.双轴连续旋转调制捷联惯导系统大失准角初始对准技术[J].导航与控制,2019,18(6):39-47. |
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| 作者姓名： | 许昊天 赵春柳 邵海俊 缪玲娟 |
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| 作者单位： | 北京理工大学自动化学院,北京100081;国家国防科技工业局军工项目审核中心,北京100039 |
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| 基金项目： | 国家自然科学基金(编号：61473039) |
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| 摘 要： | 由于可以补偿惯性器件在三个轴向上的输出误差，双轴旋转调制技术被广泛应用于捷联惯导系统(SINS)。选择了一种合理且实用的十六次序双轴转位方案，并对其调制原理和误差进行了分析。初始对准技术是捷联惯导系统的一项重要技术，其对准精度直接决定了后续导航的精度。在粗对准完成后，当姿态误差角较大时，后续的精对准误差模型呈非线性特性，故选择了滤波精度高、稳定性强的平方根容积Kalman滤波算法(SCKF)来解决这一问题。考虑到在实际对准过程中，量测噪声的统计特性易发生变化，将SCKF算法与Sage-Husa算法相结合，在传统Sage-Husa SCKF算法的基础上提出了一种改进的自适应滤波算法(ASCKF)。该算法采用QR分解来完成对噪声协方差的平方根矩阵估计，从而避免了传统Sage-Husa SCKF算法中所估噪声协方差矩阵不正定的问题。最后，通过仿真证实了ASCKF算法可被很好地应用于量测噪声统计特性发生变化的初始对准中。
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| 关 键 词： | 双轴连续旋转调制 平方根容积Kalman滤波方案 捷联惯性导航 初始对准 |
Research on Initial Alignment Technology for SINS with Large Misalignment Angle Based on Biaxial Continuous Rotation Modulation |
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| XU Hao-tian,ZHAO Chun-liu,SHAO Hai-jun and MIAO Ling-juan.Research on Initial Alignment Technology for SINS with Large Misalignment Angle Based on Biaxial Continuous Rotation Modulation[J].Navigation and Control,2019,18(6):39-47. |
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| Authors: | XU Hao-tian ZHAO Chun-liu SHAO Hai-jun and MIAO Ling-juan |
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| Affiliation: | School of Automation, Beijing Institute of Technology, Beijing 100081,National Defense Science and Technology Industry BureauMilitary Project Audit Center, Beijing 100039,School of Automation, Beijing Institute of Technology, Beijing 100081 and School of Automation, Beijing Institute of Technology, Beijing 100081 |
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| Abstract: | Biaxial rotation modulation technology is widely used in strapdown inertial navigation system (SINS) because it can compensate the output errors of three axes of inertial devices. In this paper, a reasonable and practical sixteen axis double axis transposition scheme is selected, and its modulation principle and error are analyzed. Initial alignment technology is an important technology of strapdown inertial navigation system, and its alignment accuracy directly determines the accuracy of subsequent navigation. When the attitude error angle of the coarse alignment is large, the subsequent precision alignment error model is nonlinear. The Square-root cubature Kalman filter (SCKF) with high filtering precision and strong stability is chosen to solve this problem. Considering that the statistical characteristics of measurement noise are easy to change during the actual alignment process, the SCKF algorithm is combined with the Sage-Husa algorithm and an improved adaptive filtering algorithm (ASCKF) is proposed on the basis of the traditional Sage-Husa SCKF algorithm. The algorithm uses QR decomposition to estimate the square root matrix of the noise covariance, thus avoiding the non-positive problem of the noise covariance matrix in the traditional Sage-Husa SCKF algorithm. Finally, simulation results show that the ASCKF algorithm can be applied to the initial alignment with the statistical characteristics of measurement noise. |
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| Keywords: | double axis continuous rotation modulation square-root cubature Kalman filter strapdown inertial navigation initial alignment |
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