An improved particle filtering projectile trajectory estimation algorithm fusing velocity information

Chen Liang, Qiang Shen, Zilong Deng*, Hongyun Li, Dong Liang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This study proposes an improved particle-filtering projectile trajectory estimation method that fuses velocity information to address the susceptibility to interference and large fluctuations in position and velocity measurements of a single-antenna-two-dimensional trajectory correction fuze. By considering the Doppler effect in satellite velocity measurements and the residuals between the model-derived velocity and velocity derived from the translational Doppler frequency shift, a sliding time window was established to generate velocity weight coefficients that dynamically adjust the weight of the velocity in filtering. By modifying the likelihood function, a particle-filtering algorithm was designed to achieve a fusion estimation of the projectile trajectory. Tests indicate that this method provides more accurate estimates of the position and velocity of the projectile compared to other existing methods, which can reduce the impact of velocity fluctuations to a certain extent. In addition, the computational burden is not increased and can directly replace existing mature algorithms in engineering.

Original languageEnglish
Article number115749
JournalMeasurement: Journal of the International Measurement Confederation
Volume241
DOIs
Publication statusPublished - 1 Feb 2025

Keywords

  • Doppler effect
  • Fusion state estimation
  • Particle filtering
  • Sliding time window
  • Two-dimensional trajectory correction fuze

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