Rethinking Star Selection in Celestial Navigation

P. Swaszek, R. Hartnett, K. Seals
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引用次数: 1

Abstract

In celestial navigation the altitude (elevation) angles to multiple celestial bodies are measured; these measurements are then used to compute the position of the user on the surface of the Earth. Methods described in the literature include the classical “altitude-intercept” algorithm as well as direct and iterative least-squares solutions for over determined situations. While it seems rather obvious that the user should select bright stars scattered across the sky, there appears to be no established results on the level of performance that is achievable based upon the number of stars sighted nor how the “best” set of stars might be selected from those visible. This paper addresses both of these issues by examining the performance of celestial navigation noting its similarity to the performance of GNSS systems; specifically, modern results on GDOP for GNSS are adapted to this classical celestial navigation problem.
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重新思考天文导航中的选星问题
在天体导航中,测量到多个天体的高度(仰角);然后用这些测量值来计算用户在地球表面的位置。文献中描述的方法包括经典的“高度-截距”算法,以及超确定情况下的直接和迭代最小二乘解。虽然用户应该选择散布在天空中的明亮的星星,这似乎是相当明显的,但似乎没有确定的结果表明,根据看到的星星的数量可以实现的性能水平,也没有确定的结果表明如何从可见的星星中选择“最佳”的星星。本文通过检查天体导航的性能并注意其与GNSS系统性能的相似性来解决这两个问题;具体而言,GNSS的GDOP的现代结果适用于这一经典的天体导航问题。
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