The effect of parameters of the initial data updating algorithm on the accuracy of spacecraft reentry time prediction. Issue 1 (March 2019)

• Record Type: Journal Article
• Authors: Nazarenko, А.I.; Usovik, I.V.
• Is Part Of: Journal of space safety engineering. Volume 6:Issue 1(2019)
• Page Start: 24
• Page End: 29
• Publication Date: 2019-03
• Subjects: Reentry -- Least squares technique -- Optimum filtration of measurements -- Fit span; Astronautics -- Periodicals; Space flight -- Periodicals; Space flight -- Safety measures -- Periodicals; Space flight -- Safety regulations -- Periodicals; Astronautics -- Safety measures -- Periodicals; Astronautics -- Safety regulations -- Periodicals; 629.4
• DOI: 10.1016/j.jsse.2019.01.002
• Languages: English
• ISSNs: 2468-8967

Abstract

Highlights: For the example of the Tiangong-1 SC reentry time determinations, the effect of updating algorithm parameters on the accuracy of results is estimated. The characteristics of accounting for atmospheric perturbances at "weighing" the measurements and the fit span value were considered as the algorithm parameters. In the considered example, the reentry time estimates with using the LST essentially exceeded the corresponding, more authentic estimates obtained with using the OFM. It is shown that, when the random atmospheric perturbances in the OFM technique are taken into account, the accuracy of results grows several times. Abstract: The problem under consideration has drawn attention of experts in connection with the events of large-size, dangerous spacecraft reentry. Traditionally, this problem has been solved on the basis of application of the least squares technique. In so doing, the "weighing" of measurements is carried out disregarding the random atmospheric perturbances. For the example of Tiangong-1 spacecraft reentry determination, the effect of the updating algorithm parameters on the accuracy of spacecraft reentry prediction is estimated. The characteristics of accounting for atmospheric perturbances at "weighing" the measurements and the fit span value are considered as the algorithm parameters. It is shown that, when the random atmospheric perturbances are taken into account, the accuracy of results grows several times.