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Reducing the navigational error of a flying object in space by using an integration of GPS and INS data

机译:通过整合GPS和INS数据减少飞行物体在太空中的航行误差

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The most important and applicable navigation system in space is inertial navigation system but due to the significant growth in error of velocity and position parameters of the navigation over the time in the inertial navigation systems, this system solely are not able to define the position and velocity of flying object with high accuracy. From one hand global positioning system can offer the position and velocity of flying object navigation in the space with a limited error. But satellite position system cannot determine, attitude of the flying object in the space so by integration of data, the inertia navigation system and positioning satellite can take advantage of both navigation system with less expenses. In this article, one Algorithm has been suggested to integrate of GPS and INS using extended Kalman filter to reduce the navigation error in the space. The results of simulation for 100 seconds flying according to the suggested method indicated that this integration algorithm can make the inertia navigation error convergent and finally provide the navigation goals in the flying object with high accuracy.
机译:空间中最重要和最适用的导航系统是惯性导航系统,但是由于惯性导航系统中随时间变化的导航速度和位置参数的误差显着增加,因此该系统无法单独定义位置和速度飞行物体的精度高。一方面,全球定位系统可以在有限的误差范围内提供空间中飞行物体导航的位置和速度。但是卫星定位系统无法确定空间中飞行物体的姿态,因此通过数据集成,惯性导航系统和定位卫星可以以较少的费用利用两种导航系统的优势。在本文中,提出了一种使用扩展卡尔曼滤波器将GPS和INS集成在一起的算法,以减少空间中的导航误差。根据所建议的方法对100秒飞行进行仿真,结果表明该集成算法可以使惯性导航误差收敛,并最终以较高的精度提供飞行物体的导航目标。

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