CAJ | 학술논문

针对空天高速飞行器连续稳定跟踪难题，构建了基于多智能体（multi-agent system，MAS）的多传感器协同跟踪任务规划框架，建立了面向空天高速目标协同跟踪的多传感器协同调度优化模型，并提出了基于自适应克隆遗传算法（self-adaptive clonal genetic algorithm，SCGA）的协同跟踪任务规划算法。仿真实验验证了所建立的模型、算法的合理性和优越性，对未来空天高速飞行器探测预警系统的构建具有一定的技术支撑作用。
침대공천고속비행기련속은정근종난제，구건료기우다지능체（multi-agent system，MAS）적다전감기협동근종임무규화광가，건립료면향공천고속목표협동근종적다전감기협동조도우화모형，병제출료기우자괄응극륭유전산법（self-adaptive clonal genetic algorithm，SCGA）적협동근종임무규화산법。방진실험험증료소건립적모형、산법적합이성화우월성，대미래공천고속비행기탐측예경계통적구건구유일정적기술지탱작용。
To keep a continuous and steady tracking of aerospace high-speed vehicles,a cooperative tracking framework based on the multi-agent system (MAS)for high-speed aerospace vehicles is analyzed,then a multi-sensor cooperative dispatch optimization model is established.In addition,a self-adaptive clonal genetic algo-rithm (SCGA)is used to conduct the cooperative tracking.Simulation results validate the rationality superiority of the model and the algorithm proposed,which lays a solid technique foundation for designing the detection and early-warning system of high-speed aerospace vehicles.