Unmanned Aerial Vehicle State Estimation Based on Square Root Lattice Tobit Kalman Filter

  • Yuzhao Jiao*
  • , Shuai Chang
  • , Taishan Lou
  • , Liangyu Zhao
  • , Zhiwu Chen
  • , Xuetao Li
  • *Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

The state estimation methods for nonlinear systems with censored measurements are proposed. Firstly, the Tobit-II type censored measurements equation are constructed for nonlinear system. Secondly, lattice sampling is employed to predict the latent measurement. Subsequently, the Square Root Lattice Tobit Kalman Filter (RLTKF) is derived using the square root covariance matrix obtain via QR decomposition. Finally, the algorithms are validated through the Unmanned Aerial Vehicle (UAV) cruising motion scenario, demonstrating high estimation accuracy and better robustness.

Original languageEnglish
Pages (from-to)1771-1775
Number of pages5
JournalYouth Academic Annual Conference of Chinese Association of Automation, YAC
Issue number2025
DOIs
Publication statusPublished - 2025
Externally publishedYes
Event40th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2025 - Zhengzhou, China
Duration: 17 May 202519 May 2025

Keywords

  • censored measurements
  • model parameter uncertainties
  • nonlinear system
  • Tobit-II censoring model

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