Loose navigation state algorithm of INS two-point calibration in horizontal damping state
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摘要: 为满足高精度导航要求, 提高综合校正精度, 应用扩张状态观测器设计了水平阻尼状态下惯导系统两点校正弱航态算法。简要分析了传统两点校正原理、航态约束及算法的不足, 利用扩张状态观测器实时估计惯导系统平台水平失调角, 并引入传统两点校正过程, 得出了两点校正的弱航态算法, 并对算法进行了仿真与数值检验。验证结果表明: 当载体不满足航态约束条件时, 传统两点校正估计结果大幅降低甚至发散, 而弱航态算法具有更强的适用性, 降低了载体的航态要求, 提高了综合校正精度, 试验1中东向、北向以及方位陀螺漂移校正误差分别由33.5%、51.2%、17.9%降至8.0%、1.8%、3.1%, 试验2中校正误差分别由83.7%、39.7%、77.5%降至2.3%、0.3%、1.0%。Abstract: In order to satisfy high-accuracy navigation and improve comprehensive calibration accuracy, a INS two-point calibration loose navigation state algorithm in horizontal damping state was designed by using extended state observer(ESO).The principle of traditional two-point calibration, navigation state constraint and its shortage were analyzed.The platform horizontal misalignment angles of inertial navigation system were real-timely estimated by using ESO, and traditional two-point calibration was introduced.The algorithm was simulated and numerically verified.Verification result indicates that the estimation result of traditional two-point calibration considerably reduces and even diverges when navigation state constraint can not be satisfied, neverthelessly, loose navigation state algorithm has a stronger applicability not only to reduce restrictive navigation state, but also to improve comprehensive calibration accuracy.Gyro drifts for east, north and position in experiment 1 reduce from 33.5%, 51.2%, 17.9% to 8.0%, 1.8%, 3.1% respectively, and in experiment 2, the drifts reduce from 83.7%, 39.7%, 77.5% to 2.3%, 0.3%, 1.0% respectively.
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表 1 试验1结果比较
Table 1. Results comparison of experiment 1 (°)·h-1
陀螺漂移 设定值 未补偿 补偿后 εx 0.01 0.006 655 0.010 800 εy 0.015 116 0.010 180 εz 0.011 790 0.009 690 
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表 2 试验2结果比较
Table 2. Results comparison of experiment 2 (°)·h-1
陀螺漂移 设定值 未补偿 补偿后 εx 0.01 0.001 630 0.010 230 εy 0.006 030 0.010 030 εz 0.017 750 0.010 100
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