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

Qian Hua-Ming, Sun Long
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Abstract

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.
基于MME/KF算法的SINS/SRCNS组合导航方法
传统的SINS/CNS组合导航系统受水平基准的限制,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/恒星折射天体导航系统组合导航方法(SINS/SRCNS)。采用最小模态误差估计(MME)和反向推理算法对测量方程中存在不确定的模型误差进行估计。然后利用卡尔曼滤波对系统状态进行估计,整个过程形成了MME/KF算法。仿真结果表明,该方法不仅能准确估计陀螺漂移,还能修正加速度计偏置引起的导航误差,同时抑制速度和位置误差的发散,是提高定位精度的一种实用方法。
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