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In-Motion Initial Alignment Method Based on Multi-Source Information Fusion for Special Vehicles.

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Summary

This study introduces a robust moving-base autonomous alignment for vehicular inertial navigation systems, enhancing accuracy and adaptability in GPS-denied battlefield environments through multi-source data fusion and fault-tolerant strategies.

Keywords:
fault diagnosis and isolationfederal Kalman filterin-motion alignmentmulti-source information fusionstrapdown inertial navigation system

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Area of Science:

  • Navigation Systems Engineering
  • Robotics and Autonomous Systems
  • Sensor Fusion and Signal Processing

Background:

  • Traditional stationary base alignment methods are insufficient for dynamic battlefield conditions.
  • Vehicular inertial navigation systems require rapid initial alignment, especially in Global Navigation Satellite System (GNSS)-denied environments.
  • Complex battlefield scenarios pose significant challenges to navigation system accuracy and reliability.

Purpose of the Study:

  • To develop a robust moving-base autonomous alignment approach for vehicular inertial navigation systems.
  • To enhance navigation parameter calculation and system reliability under GNSS-denied conditions.
  • To improve the adaptability and fault tolerance of navigation systems in complex operational scenarios.

Main Methods:

  • Implemented a federal Kalman filter-based multi-sensor fusion architecture integrating odometer, laser Doppler velocimeter, and Strapdown Inertial Navigation System (SINS) data.
  • Developed a dual-mode fault diagnosis and isolation mechanism for rapid sensor failure identification and system reconfiguration.
  • Proposed an environmentally adaptive dynamic alignment strategy for intelligent selection of optimal alignment modes based on real-time conditions.

Main Results:

  • Significantly improved the accuracy of vehicle-mounted alignment during motion.
  • Achieved accurate identification, effective isolation, and reconstruction of random incidental sensor faults.
  • Demonstrated enhanced system adaptability and robustness in complex operational scenarios.

Conclusions:

  • The proposed method offers an innovative solution for rapid deployment of vehicles in GNSS-denied environments.
  • The fault-tolerant mechanisms and adaptive strategies provide critical insights for next-generation intelligent navigation systems.
  • This research addresses the urgent demand for autonomous alignment in challenging military applications.