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A SIMULATION TOOL FOR SPACE SITUATIONAL AWARENESS: NEAR EARTH OBJECTS

机译:空间状况感知的仿真工具:近地物体

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A simulation tool for Near Earth Objects (NEO) orbit determination by means of optical measurements is presented. The peculiarity of the simulator is the use of high order methods based on Differential Algebra (DA) techniques. State-of-the art tools are mostly based on either linear methods or nonlinear Monte Carlo simulations. The main advantage of linear methods stays in their problem simplification, but their accuracy drops off rapidly for large uncertainty sets. Classical Monte Carlo simulations provide true statistics, but are computationally intensive. DA techniques are used to overcome the above issues, supplying the tools to compute arbitrary order derivatives of functions within a computer environment with limited computational effort. The availability of the high order Taylor expansions is exploited to manage problem uncertainties. The tool includes a simulator of optical observations, DA-based algorithms for NEO preliminary and accurate orbit determination. Angular measurements simulation is based on the propagation in time of initial asteroid state through multi-body dynamics; aberration, precession and nutation effects may be taken into account by the simulator. Preliminary orbit determination (POD) is based on Lambert's and Kepler's problems and uses the real solutions of the classical Gauss method 8th order polynomial as first guesses of an iterative procedure. A better convergence with respect to Gauss method is achieved. Observations uncertainties are analytically mapped to the phase space as high-order multivariate Taylor polynomials. When more than three observations are available, the tool applies a high order Extended Kalman filter, initialized by the POD solution. The uncertainties related to the POD are propagated forward in time by exploiting the high order expansion of the flow of the dynamics. Thus, the initial covariance is nonlinearly and analytically propagated up to the next measurement. The performance of the tool is analysed by running the algorithms on a list of real Near Earth Asteroids and simulated topocentric observations.
机译:提出了一种用于通过光学测量确定近地物体(NEO)轨道的仿真工具。模拟器的独特之处在于使用了基于微分代数(DA)技术的高阶方法。最新的工具主要基于线性方法或非线性蒙特卡洛模拟。线性方法的主要优点在于简化了问题,但对于较大的不确定性集,其准确性迅速下降。经典的蒙特卡洛模拟提供了真实的统计信息,但是计算量很大。 DA技术用于克服上述问题,提供了使用有限的计算量来计算计算机环境中函数的任意阶导数的工具。利用高阶泰勒展开式来管理问题的不确定性。该工具包括光学观测模拟器,用于NEO初步和准确确定轨道的基于DA的算法。角测量模拟是基于初始小行星状态通过多体动力学的传播;模拟器可以考虑像差,进动和章动效应。初步轨道确定(POD)基于朗伯和开普勒问题,并使用经典高斯方法8阶多项式的实解作为迭代过程的第一个猜测。就高斯方法而言,实现了更好的收敛性。观测不确定性作为高阶多元泰勒多项式解析地映射到相空间。当三个以上的观测值可用时,该工具将应用由POD解决方案初始化的高阶扩展卡尔曼滤波器。通过利用动力学流的高阶展开,与POD相关的不确定性会及时向前传播。因此,初始协方差被非线性地和解析地传播到下一次测量。通过在一系列实际的近地小行星和模拟的地形中心观测资料上运行算法来分析该工具的性能。

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