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Abstract <p>The article discusses the problem of estimating the spacecraft trajectory parameters based on data provided by GNSS (Global Navigation Satellite System) receiver and onboard spacecraft motion prediction algorithms. The traditional approach to solving the mentioned problem relies on Kalman filtering techniques for estimating the spacecraft’s coordinates and velocity. In this case the navigation algorithms in the onboard computer must meet the technical requirements for maximum reduction in computational load. The paper proposes a method of decomposition for onboard integration algorithm using three parallel second-order filters, which significantly reduces the computational load of the algorithm while maintaining the accuracy.</p>

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Decomposed Spacecraft Motion Estimation Algorithm Using GNSS Data

  • 期刊论文

  • 发表日期：

    2025年6月1日

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  • A. A. Golovan,
  • I. M. Markov,
  • I. V. Solov’ev,
  • M. A. Shatskii

摘要

Abstract

The article discusses the problem of estimating the spacecraft trajectory parameters based on data provided by GNSS (Global Navigation Satellite System) receiver and onboard spacecraft motion prediction algorithms. The traditional approach to solving the mentioned problem relies on Kalman filtering techniques for estimating the spacecraft’s coordinates and velocity. In this case the navigation algorithms in the onboard computer must meet the technical requirements for maximum reduction in computational load. The paper proposes a method of decomposition for onboard integration algorithm using three parallel second-order filters, which significantly reduces the computational load of the algorithm while maintaining the accuracy.