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Attitude Tracking Algorithm Using GNSS Measurements from Short Baselines.

Fedor Kapralov1, Alexander Kozlov1

  • 1Faculty of Mechanics and Mathematics, Lomonosov Moscow State University, 119991 Moscow, Russia.

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Summary
This summary is machine-generated.

This study introduces a new algorithm for precise attitude determination using Global Navigation Satellite System (GNSS) phase measurements. The method simplifies complex calculations, enabling efficient and accurate real-time tracking for navigation platforms.

Keywords:
attitude determinationglobal navigation satellite system (GNSS)integer ambiguity resolution (IAR)

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Area of Science:

  • Geomatics Engineering
  • Navigation Systems
  • Satellite Technology

Background:

  • Attitude determination is crucial for navigation platforms.
  • Global Navigation Satellite System (GNSS) phase measurements offer high accuracy.
  • Integer ambiguities in GNSS phase data present a significant computational challenge.

Purpose of the Study:

  • To develop a computationally efficient algorithm for attitude determination using GNSS.
  • To address the nonlinear, non-convex optimization problem associated with integer ambiguities.
  • To improve real-time attitude tracking accuracy for navigation systems.

Main Methods:

  • Proposed a novel algorithm reducing the attitude estimation problem to a linear integer least squares problem.
  • Introduced a new a priori model for GNSS measurement error variance.
  • Utilized multi-antenna GNSS phase measurements for attitude tracking.

Main Results:

  • The new algorithm significantly reduces computational demands compared to traditional methods.
  • Demonstrated promising results on a real-world dataset from a multi-antenna GNSS system.
  • Achieved accurate attitude determination with sub-degree precision for sub-meter baselines.

Conclusions:

  • The developed algorithm offers an efficient and accurate solution for GNSS-based attitude determination.
  • The method simplifies complex integer ambiguity resolution in attitude estimation.
  • This approach has the potential to enhance real-time navigation system performance.