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GPS/SINS Speed Integral Matching Alignment Based on Improved Adaptive UKF

机译:基于改进自适应UKF的GPS / SINS速度积分匹配对准

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To solve the problem of system error and environmental interference of MEMS inertial sensor, which make SINS cannot quickly and accurately alignment, a GPS/SINS speed 'integral' matching alignment method is designed. Firstly, the GPS velocity measurement values are used to assits the SINS for coarse alignment in this paper. Then, speed integral matching fine alignment is performed. Establishing the alignment model, the solution speed of the SINS is corrected by the least squares curve fitting method and the arm effect is compensated for the GPS speed signal before filtering. Using the unscented Kalman filter (UKF) and the improved adaptive UKF to achieve the fine alignment respectively. Outdoor experiments and simulation's results show that the improved adaptive UKF can achieve higher alignment accuracy and speed. Compared with the common UKF, the accuracy of the east, north and up misalignment angles is inhanced by 0.12°, 0.03° and 0.19°, respectively. The alignment time is shortened by 20s, 10s and 25s, respectively. The above work can provide a reference for AUV accurate navigation.
机译:为解决MEMS惯性传感器的系统误差和环境干扰问题,这些问题使SINS无法快速,准确地对准,设计了一种GPS / SINS速度“积分”匹配对准方法。首先,本文利用GPS速度测量值对SINS进行粗调。然后,执行速度积分匹配微对准。建立对准模型,通过最小二乘曲线拟合法校正捷联惯导系统的解速度,并在滤波前对GPS速度信号补偿臂效应。使用无味卡尔曼滤波器(UKF)和改进的自适应UKF分别实现精细对准。户外实验和仿真结果表明,改进的自适应UKF可以实现更高的对准精度和速度。与普通UKF相比,东,北和上偏心角的精度分别提高了0.12°,0.03°和0.19°。对准时间分别缩短了20s,10s和25s。以上工作可为AUV的精确导航提供参考。

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