Cooperative Location Method for Leader-Follower UAV Formation Based on Follower UAV's Moving Vector.

Area of Science:

• Aerospace Engineering
• Robotics
• Navigation Systems

Background:

• Traditional Unmanned Aerial Vehicle (UAV) formation cooperative positioning (CP) relies on multiple known leader UAV positions, limiting its applicability when leader data is scarce.
• Accurate positioning of a follower UAV is challenging with only single-distance measurements to a leader UAV.

Purpose of the Study:

• To develop a novel CP method for UAVs that overcomes the limitations of traditional algorithms when the number of known leader UAV positions is restricted.
• To enhance the positioning accuracy of follower UAVs by utilizing their own moving vector and an improved extended Kalman filter.

Main Methods:

• A cooperative positioning method is proposed for a minimum cooperative unit (one leader, one follower UAV) using the follower UAV's moving vector.
• The follower UAV's Inertial Navigation System (INS) is modeled, and its position, velocity, and heading observation equations are constructed.
• An improved extended Kalman filter is employed for state vector estimation to enhance positioning accuracy.
• A two-state Markov chain is used to assess the availability of relative distance information from the leader UAV, addressing potential datalink interference.

Main Results:

• The proposed method effectively utilizes the follower UAV's moving vector to improve positioning accuracy, even with limited leader UAV information.
• The improved extended Kalman filtering enhances the estimation of the follower UAV's state vector.
• The algorithm demonstrates robust performance in handling intermittent relative distance measurements.

Conclusions:

• The developed CP method based on the follower UAV's moving vector offers a viable solution for high-precision positioning in scenarios with limited leader UAV data.
• The integration of INS modeling, improved Kalman filtering, and a Markov chain for datalink assessment significantly boosts follower UAV positioning accuracy and reliability.