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S-asteroid spectral interpreter (SASI): spectral analysis system for the Near-Earth Asteroid Rendezvous (NEAR) mission using a neural network preprocessor

机译:S-asteroid光谱解释器(SASI):使用神经网络预处理器的近地小行星交会(NEAR)任务的光谱分析系统

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Abstract: The surfaces of asteroids consist of mineral grains mixed on scales of 10-110's of micrometers where linear mixing rules for near-IR spectra do not apply. Further, the spectral properties of the mineral components are strong nonlinear functions of grain size and chemical composition. Detailed models of these nonlinear properties exist, but are not amenable to analytic inversion, requiring relatively inefficient iterative solutions to extract physical data from reflectance spectra. However, the NASA Near-Earth Asteroid Rendezvous mission soon to orbit the asteroid Eros requires near real time spectral analysis of near-IR spectral data for mission operations planning. The S- Asteroid Spectral Interpreter is a software system which includes a neural network which has been trained to invert the nonlinear physical model, and conventional gradient descent algorithm which refines the output of the neural network to arrive at a rapid analysis of input spectra. !7
机译:摘要:小行星的表面由以10-110微米的尺度混合的矿物颗粒组成,而近红外光谱的线性混合规则不适用。此外,矿物成分的光谱特性是晶粒尺寸和化学成分的强非线性函数。这些非线性特性的详细模型已经存在,但不适合解析反演,因此需要相对低效的迭代解决方案才能从反射光谱中提取物理数据。但是,要使小行星爱神星(Eros)绕轨道飞行的NASA近地小行星交会任务需要近红外光谱数据的近实时光谱分析,以进行任务运营规划。 S-Asteroid光谱解释器是一个软件系统,其中包括训练有素的神经网络可以逆转非线性物理模型,以及常规的梯度下降算法,可以优化神经网络的输出以快速分析输入光谱。 !7

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