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Optimal Linear Estimation of Binary Star Parameters

机译:双星参数的最优线性估计

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We propose a new post-processing technique for the detection of faint companions and the estimation of their parameters from adaptive optics (AO) observations. We apply the optimal linear detector, which is the Hotelling observer, to perform detection, astrometry and photometry on real and simulated data. The real data was obtained from the AO system on the 3m Lick telescope .The Hotelling detector, which is a prewhitening matched filter, calculates the Hotelling test statistic which is then compared to a threshold. If the test statistic is greater than the threshold the algorithm decides that a companion is present. This decision is the main task performed by the Hotelling observer. After a detection is made the location and intensity of the companion which maximise this test statistic are taken as the estimated values.We compare the Hotelling approach with current detection algorithms widely used in astronomy. We discuss the use of the estimation receiver operating characteristic (EROC) curve in quantifying the performance of the algorithm with no prior estimate of the companion's location or intensity. The robustness of this technique to errors in point spread function (PSF) estimation is also investigated.
机译:我们提出了一种新的后处理技术,用于检测微弱的同伴并从自适应光学(AO)观测值估计其参数。我们应用最佳线性探测器(即Hotelling观测器)对真实和模拟数据执行探测,天文测量和光度测量。真实数据是从3m Lick望远镜上的AO系统获得的。 作为预白化匹配滤波器的Hotelling检测器计算出Hotelling测试统计量,然后将其与阈值进行比较。如果测试统计量大于阈值,则算法确定存在同伴。该决定是Hotelling观察员执行的主要任务。进行检测后,将使该测试统计信息最大化的同伴的位置和强度作为估计值。 我们将Hotelling方法与天文学中广泛使用的当前检测算法进行了比较。我们讨论了使用估计接收器操作特性(EROC)曲线来量化算法的性能,而无需事先估计伴星的位置或强度。还研究了该技术对点扩展函数(PSF)估计误差的鲁棒性。

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