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首页> 外文期刊>Applied Soft Computing >An ANN embedded RTS smoother for an INS/GPS integrated Positioning and Orientation System
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An ANN embedded RTS smoother for an INS/GPS integrated Positioning and Orientation System

机译:用于INS / GPS集成定位和定向系统的ANN嵌入式RTS平滑器

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摘要

Digital mobile mapping, which integrates digital imaging with direct geo-referencing, has developed rapidly over the past fifteen years. The direct geo-referencing is the determination of time variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning by GPS and inertial navigation using an IMU. They are usually integrated in such a way that the GPS receiver is the main position sensor, while the IMU is the main orientation sensor. KF is considered the optimal estimation tool for teal-time INS/GPS integrated kinematic positioning and orientation determination. In post-mission processing, on the other hand, data from the whole mission can be used to estimate the trajectory. When filtering is used in the first step, an optimal smoothing algorithm can be applied to achieve higher accuracy for mobile mapping applications. An intelligent and hybrid scheme consisting of an ANN and KF is proposed to overcome the limitations of KF and to improve the performance of an INS/GPS integrated system from a previous study. However, the accuracy requirements of general mobile mapping applications cannot be achieved easily even by using an ANN-KF scheme. Therefore, this study proposes an ANN embedded RTS backward smoother to enhance the overall accuracy of POS parameters for a tactical grade INS/GPS integrated system in a post-mission mode. Combing the tactical grade INS/GPS integrated system and intelligent POS scheme proposed in this study, a cheap but reasonably accurate POS can be anticipated.
机译:在过去的15年中,将数字成像与直接地理参考相结合的数字移动地图已经得到了快速发展。直接地理参考是确定移动数字成像器的时变位置和方向参数。今天,用于此目的的最常见技术是GPS卫星定位和使用IMU的惯性导航。它们通常以GPS接收器为主要位置传感器而IMU为主要方向传感器的方式集成。 KF被认为是青色时间INS / GPS集成运动定位和方向确定的最佳估计工具。另一方面,在任务后处理中,整个任务的数据可用于估计轨迹。在第一步中使用过滤时,可以应用最佳平滑算法来为移动地图应用程序实现更高的精度。提出了一种由ANN和KF组成的智能混合方案,以克服KF的局限性并提高先前研究中INS / GPS集成系统的性能。但是,即使使用ANN-KF方案,也无法轻松实现一般移动地图应用程序的精度要求。因此,本研究提出了一种ANN嵌入式RTS后向平滑器,以提高任务后模式下战术级INS / GPS集成系统的POS参数的整体准确性。结合本研究中提出的战术级INS / GPS集成系统和智能POS方案,可以预期一种便宜而合理的POS。

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