A cooperative interference resource allocation method based on improved firefly algorithm

To deal with the radio frequency threat posed by modern complex radar networks to aircraft, we researched the unmanned aerial vehicle (UAV) formations radar countermeasures, aiming at the solution of radar jamming resource allocation under system countermeasures. A jamming resource allocation method based on an improved firefly algorithm (FA) is proposed. Firstly, the comprehensive factors affecting the level of threat and interference efficiency of radiation source are quantified by a fuzzy comprehensive evaluation. Besides, the interference efficiency matrix and the objective function of the allocation model are determined to establish the interference resource allocation model. Finally, A mutation operator and an adaptive heuristic are integtated into the FA algorithm, which searches an interference resource allocation scheme. The simulation results show that the improved FA algorithm can compensate for the deficiencies of the FA algorithm. The improved FA algorithm provides a more sci-entific and reasonable decision-making plan for aircraft mission allocation and can effectively deal with the battlefield threats of the enemy radar network. Moreover, in terms of convergence accuracy and speed as well as algorithm stability, the improved FA algorithm is superior to the simulated annealing algorithm (SA), the niche genetic algorithm (NGA), the improved discrete cuckoo algorithm (IDCS), the mutant firefly algorithm (MFA), the cuckoo search and fireflies algorithm (CSFA), and the best neighbor firefly algorithm (BNFA).     

窄带环境下的远程分布式服务调用优化与验证方法

指挥控制系统是现代化作战的核心环节和重要支撑,通过对网络化的作战需求分析,针对窄带环境下实现分布式服务远程访问存在错误率高和延时长等问题,应用精简协议、压缩数据包和大小包数据的动态拆分、聚合等方法,提高分布式指挥控制系统在窄带环境下的适应性.通过搭建不同的窄带模拟环境,验证了提出的优化方法能够有效提高服务在窄带环境下的注册、被发现和被调用的能力.