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Research on Nonlinear Error Compensation and Intelligent Optimization Method for UAV Target Positioning.

Yinglei Li1, Qingping Hu1, Shiyan Sun1

  • 1Graduate School, Naval University of Engineering, 717 Jiefang Road, Qiaokou District, Wuhan 430030, China.

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Summary
This summary is machine-generated.

This study introduces an improved raccoon optimization algorithm (KYCOA) to enhance unmanned aerial vehicle (UAV) target positioning accuracy by minimizing errors from nonlinear perturbations and coordinate transformations.

Keywords:
Monte Carlo simulationairborne optoelectronic podserror allocationtarget localization

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Area of Science:

  • Aerospace Engineering
  • Robotics
  • Optimization Algorithms

Background:

  • High-precision target positioning in UAVs is challenged by nonlinear perturbations and cumulative coordinate transformation errors.
  • Multi-source error coupling degrades positioning accuracy in unmanned aerial vehicle (UAV) target localization.

Purpose of the Study:

  • To develop an effective error allocation method for improving UAV target positioning accuracy.
  • To address the degradation of positioning accuracy caused by multi-source error coupling in UAVs.

Main Methods:

  • Established a multi-coordinate system transformation model to analyze nonlinear error transfer.
  • Linearized error transfer using Taylor expansion to derive a synthetic error model.
  • Proposed the improved raccoon optimization algorithm (KYCOA) with enhanced population diversity and position updating mechanisms.

Main Results:

  • KYCOA demonstrated significant reductions in positioning error distance compared to COA, GWO, and WOA in simulations.
  • Real flight tests showed an average reduction of over 40% in target point localization error using KYCOA.
  • The proposed method effectively improved target localization accuracy and robustness in UAVs.

Conclusions:

  • The KYCOA algorithm offers a robust solution for optimizing error allocation in UAV target positioning.
  • The method significantly enhances positioning accuracy by mitigating nonlinear perturbations and coordinate transformation errors.
  • KYCOA proves effective in real-world UAV applications, improving target localization performance.