Cooperative Navigation for Cross-Platform Dual-SINS Based on Relative Range and Angle Measurements

Area of Science:

• Robotics and Autonomous Systems
• Navigation and Positioning
• Sensor Fusion

Background:

• Single-platform Inertial Navigation Systems (INS) suffer from rapidly divergent positioning errors in Global Navigation Satellite System (GNSS)-denied environments.
• Accurate navigation in GNSS-denied scenarios is critical for applications like ground vehicular positioning.

Purpose of the Study:

• To propose and evaluate a cross-platform cooperative navigation method for improving INS accuracy in GNSS-denied environments.
• To investigate the observability of the cooperative navigation system under various motion strategies.

Main Methods:

• Developed a cooperative navigation method utilizing relative range and angle measurements between two strapdown inertial navigation systems (SINS).
• Employed Fisher Information Matrix (FIM) right null-space analysis and Singular Value Decomposition (SVD) to assess system observability.
• Conducted experiments comparing cooperative navigation with autonomous INS mode.

Main Results:

• Relative range and angle measurements enabled effective estimation of inertial sensor biases for two SINS moving along a simple trajectory.
• Experimental results showed significant improvements in average positioning accuracy: 77.4% and 68.4% for the two SINS after 3 hours of cooperative navigation.
• The proposed method achieved substantial accuracy gains without requiring high-precision benchmarks or complex motion trajectories.

Conclusions:

• The cross-platform cooperative navigation method effectively mitigates positioning errors in GNSS-denied environments.
• The approach simplifies system complexity and motion requirements, offering an easy-to-implement solution for ground vehicles and other cooperative navigation tasks.
• Relative measurements and simple planar motion are sufficient for accurate cooperative navigation, enhancing robustness and practicality.