Research on Low-Cost Attitude Estimation for MINS/Dual-Antenna GNSS Integrated Navigation Method

Area of Science:

• Robotics and Autonomous Systems
• Navigation and Control Systems
• Sensor Fusion Technology

Background:

• High-precision navigation is crucial for unmanned vehicles.
• Existing high-precision sensors are often prohibitively expensive.
• There is a need for cost-effective, accurate navigation solutions.

Purpose of the Study:

• To propose a low-cost, high-precision navigation system for unmanned vehicles.
• To integrate dual-antenna Global Navigation Satellite System (GNSS) with Micro-electromechanical Systems-Inertial Navigation System (MINS).
• To enhance navigation accuracy by leveraging dual-antenna GNSS data.

Main Methods:

• A novel combination method using dual-antenna GNSS and MINS was developed.
• Extended Kalman Filtering (EKF) was employed for data fusion.
• The system was implemented on an ARM+FPGA platform.
• Static and dynamic tests were conducted using a SPAN-CPT reference system.

Main Results:

• The integrated GNSS/MINS system demonstrated improved accuracy in velocity, position, and attitude angles.
• Yaw angle accuracy reached 0.2° RMS.
• Pitch angle accuracy achieved 0.3° RMS.
• Feasibility was verified through simulations and real-world testing.

Conclusions:

• The proposed dual-antenna GNSS/MINS integration offers a cost-effective solution for high-precision navigation.
• This method significantly enhances the accuracy of unmanned vehicle navigation systems.
• The system is suitable for deployment in unmanned vehicles requiring precise positioning and orientation.