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This paper introduces a novel height estimation method for unmanned aerial vehicle (UAV) based on set-membership filter (SMF) and constrained zonotope. Firstly, we introduce the concept of uncertain variables to establish the equation of state and the framework of the SMF algorithm. Then, the dynamics are modeled considering the tilt angle of the UAV, and the measurement equations are derived. On this basis, a UAV height estimation algorithm with guaranteed optimality and small computational effort is proposed. The outcomes from the real-world experiment illustrate that the proposed method exhibits superior overall estimation performance and imposes more stringent constraints on the estimation error compared to the Kalman filter.

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An Unmanned Aerial Vehicle Height Estimation Method: Based on Set-Membership Filter and Constrained Zonotope

  • 会议论文

  • 发表日期：

    2025年

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  • Cheng Li,
  • Xujie Qin,
  • Yute Xiao,
  • Liuhao Sheng

摘要

This paper introduces a novel height estimation method for unmanned aerial vehicle (UAV) based on set-membership filter (SMF) and constrained zonotope. Firstly, we introduce the concept of uncertain variables to establish the equation of state and the framework of the SMF algorithm. Then, the dynamics are modeled considering the tilt angle of the UAV, and the measurement equations are derived. On this basis, a UAV height estimation algorithm with guaranteed optimality and small computational effort is proposed. The outcomes from the real-world experiment illustrate that the proposed method exhibits superior overall estimation performance and imposes more stringent constraints on the estimation error compared to the Kalman filter.