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SINS/SRCNS Integrated Navigation Method Based on MME/KF Algorithm

机译:基于MME / KF算法的SINS / SRCNS组合导航方法

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摘要

The positioning accuracy of traditional SINS/CNS integrated navigation system is low, because of the limitation of level benchmark. So strap-down inertial navigation system/stellar refraction celestial navigation system integrated navigation method (SINS/SRCNS) based on starlight refraction method is proposed. The model errors which are uncertain exist in measurement equation are estimated by Minimum Mode error Estimation (MME) and backward inference algorithm. Then the Kalman Filter is used to estimate system's states, this entire process formed the MME/KF algorithm. The simulation results indicated that, the proposed method is not only able to estimate the gyro drift exactly, but also to correct the navigation error caused by the accelerometer bias, and bate the divergence of speed and position error ulteriorly, therefore it is a practical method to improve the positioning accuracy.
机译:由于水平基准的局限性,传统的SINS / CNS组合导航系统的定位精度较低。为此,提出了基于星光折射法的捷联惯性导航系统/星折射天文导航系统组合导航方法(SINS / SRCNS)。测量方程中存在不确定的模型误差,通过最小模态误差估计(MME)和反向推理算法进行估计。然后将卡尔曼滤波器用于估计系统状态,整个过程形成了MME / KF算法。仿真结果表明,该方法不仅能够准确估计陀螺仪的漂移,而且能够校正由加速度计偏差引起的导航误差,并克服了速度和位置误差的发散性,是一种实用的方法。提高定位精度。

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