Radar Measurement Simulation of UAV Group Targets Using Policy Consistency Algorithm

Consensus theory plays a crucial role in achieving formation control for unmanned aerial vehicle (UAV) swarms. While traditional consistency algorithms are commonly employed in two-dimensional spaces, the practical scenarios often involve three-dimensional motion modeling, necessitating continuous formation adjustments to adapt to intricate combat missions. Additionally, the interaction among targets during their movements presents a challenge for the implementation of consistency algorithms. To address these challenges, this paper presents a comprehensive study of UAV control and radar measurements in the context of swarm operations. The formation control system is simplified into three control systems: velocity, heading angle, and altitude. A novel consensus-based cooperative formation control algorithm is proposed, considering the formation constraints and desired state. Furthermore, the process of radar measurement generation faces challenges such as complex noise interference, missed detections, and false alarms. The paper proposes a radar measurement generation method based on the position, azimuth, and elevation angles of the UAV formation. The simulation results validate that the proposed algorithm can effectively form and maintain a stable and highly accurate formation even in complex environments.

I. Introduction

In recent years, radar measurement simulation for group targets has been widely applied in diverse domains, such as military operations and traffic regulation [1]. Group targets are defined as collections of multiple targets that share similar dynamic characteristics, making it challenging to distinguish them within a given time frame, such as a radar cycle. Examples of group targets include dense unmanned aerial vehicle (UAV) formations, flocks of birds, and swarms of insects. Among them, UAV swarms have become indispensable components on modern battlefields due to their advantageous mobility, cost-effectiveness, and adaptability to diverse environments. Consequently, the study of UAV swarm formation and collective movement has received significant attention in the field of UAV control, with notable projects such as the US Gremlins program and the Perdix micro-UAV project [2] [3].