基于线性卡尔曼滤波的扩展时间飞行SINS/CNS集成算法及仿真

2015 IEEE International Conference on Communication Software and Networks (ICCSN) Pub Date : 2015-06-06 DOI:10.1109/ICCSN.2015.7296122

K. Badshah, Qin Yongyuan, Jinliang Zhang

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引用次数: 16

摘要

设计并研究了捷联惯导/天体导航系统的鲁棒积分算法。该集成方案的主要目标是在长时间导航任务中估计和修正捷联惯导系统的不可接受误差。本研究采用窄视场(NFOV)星跟踪器作为中枢神经系统辅助装置。设计了估计平台不对准角的数学模型，并进行了不同坐标系的变换。提出了一种包含位置误差的修正测量模型的线性化卡尔曼滤波器(LKF)，用于捷联惯导系统和中枢惯导系统的数据融合。最后，仿真结果表明了该积分算法在长时间飞行中对捷联惯导系统误差估计和修正的完整性和有效性。

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SINS/CNS integration algorithm and simulations for extended time flights using linearized Kalman filtering

A robust integration algorithm for Strapdown Inertial Navigation System/Celestial Navigation System (SINS/CNS) is designed and investigated in this paper. The main objective of the developed integration scheme is the estimation and correction of unacceptable SINS' errors in long time navigation missions. A Narrow Field of View (NFOV) star tracker is used as a CNS aid in this study. A mathematical model is designed to estimate the platform misalignment angles and transformations of different frames are exercised. Linearized Kalman Filter (LKF), with a modified measurement model, encompassing the position errors, is proposed for fusing the data of SINS and CNS. Finally, simulation results are produced to show the integrity and validity of the integration algorithm for estimation and correction of the SINS errors in extended time flights.

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2015 IEEE International Conference on Communication Software and Networks (ICCSN)

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