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Multiple Model-Based Synchronization Approaches for Time Delayed Slaving Data in a Space Launch Vehicle Tracking System

机译:空间发射车跟踪系统中的多种基于模型的延迟奴役数据的同步方法

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摘要

Due to the inherent characteristics of the flight mission of a space launch vehicle (SLV), which is required to fly over very large distances and have very high fault tolerances, in general, SLV tracking systems (TSs) comprise multiple heterogeneous sensors such as radars, GPS, INS, and electrooptical targeting systems installed over widespread areas. To track an SLV without interruption and to hand over the measurement coverage between TSs properly, the mission control system (MCS) transfers slaving data to each TS through mission networks. When serious network delays occur, however, the slaving data from the MCS can lead to the failure of the TS. To address this problem, in this paper, we propose multiple model-based synchronization (MMS) approaches, which take advantage of the multiple motion models of an SLV. Cubic spline extrapolation, prediction through an α-β-γ filter, and a single model Kalman filter are presented as benchmark approaches. We demonstrate the synchronization accuracy and effectiveness of the proposed MMS approaches using the Monte Carlo simulation with the nominal trajectory data of Korea Space Launch Vehicle-I.
机译:由于空间发射车辆(SLV)的飞行特性的固有特性,这是在非常大的距离上飞行并且具有非常高的容错公差,通常,SLV跟踪系统(TSS)包括多个异构传感器,例如雷达,GPS,INS和电光瞄准系统安装在广泛的区域上。在不中断的情况下跟踪SLV并正确地处理TSS之间的测量覆盖,使命控制系统(MCS)通过任务网络将奴隶数据传输到每个TS。然而,当发生严重的网络延迟时,来自MCS的奴隶数据可能导致TS的故障。为了解决这个问题,在本文中,我们提出了多种基于模型的同步(MMS)方法,这利用了SLV的多个运动模型。立方样条推外,通过α-β-γ滤波器预测,以及单个模型卡尔曼滤波器作为基准方法。我们展示了使用Monte Carlo仿真的所提出的MMS方法的同步精度和有效性,其中韩国空间发射车辆的标称轨迹数据 - I。

著录项

  • 作者

    Haryong Song; Yongtae Choi;

  • 作者单位
  • 年度 2016
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  • 原文格式 PDF
  • 正文语种 eng
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