基于互相关协同的无人机集群区域覆盖监视优化方法

An Optimization Method of Coverage and Monitoring with UAV Swarm Based on Cross-Correlation Cooperation

在电磁频谱监测领域,现阶段面向区域覆盖监视的无人机集群协同优化方法存在覆盖监视能力不足、实时性差等问题。针对上述问题,提出了一种基于互相关协同的无人机集群区域覆盖监视优化方法。首先,利用信号互相关原理和相关检测覆盖性能建立了多机相关检测可覆盖监视面积计算模型;其次,通过引入自适应非线性权重等策略,提出了基于自适应非线性权重的并行混合粒子群协同优化算法;最后,以多机相关检测可覆盖监视面积为区域覆盖监视的优化目标函数,迭代优化无人机的相对位置,得到面向区域覆盖监视的集群最优拓扑构型和最大可覆盖监视面积。仿真验证结果表明,与其他方法相比,本文方法能够将可覆盖监视范围提升60%以上,将优化收敛速度减少至1.05 s。

In the field of electromagnetic spectrum monitoring,existing optimization methods for region coverage and monitoring with cooperative unmanned aerial vehicle(UAV) swarm have many challenges,such as insufficient coverage and monitoring capability and poor real-time performance.To solve these problems,an optimization method of coverage and monitoring with UAV swarm based on cross-correlation cooperation is proposed.Firstly,based on the principle of signal cross-correlation and the correlation detection coverage performance,the optimization objective function for region coverage and monitoring is constructed;Secondly,by introducing the adaptive nonlinear weight and other strategies,an adaptive parallel hybrid particle swarm optimization algorithm is proposed;Finally,taking the coverage area of UAV swarm correlation detection as the optimization objective function of regional coverage and monitoring,the relative position of UAV is iteratively optimized,and the optimal topology of swarm for regional coverage and monitoring is obtained.The simulation results show that compared with other methods,this method can increase the coverage monitoring range by more than 60% and reduce the optimization convergence speed to 1.05 s.