D-SOAR PLUS G 40000 W特高功率高速光纤激光切割机,主要针对高端客户精心配置,整机由瑞士百超集团技术团队领衔设计,主要零部件采用原装进口品牌,具有切割精度高、速度更快、操作更简单、使用成本更低和切割材料更广泛等特点,为客户提...D-SOAR PLUS G 40000 W特高功率高速光纤激光切割机,主要针对高端客户精心配置,整机由瑞士百超集团技术团队领衔设计,主要零部件采用原装进口品牌,具有切割精度高、速度更快、操作更简单、使用成本更低和切割材料更广泛等特点,为客户提供了稳定的激光切割性能,减少了板材浪费,提高了生产能力。展开更多
For coping with the multiple target tracking in the presence of complex time-varying environments and unknown target information, a time resource management scheme based on chance-constraint programming(CCP) employi...For coping with the multiple target tracking in the presence of complex time-varying environments and unknown target information, a time resource management scheme based on chance-constraint programming(CCP) employing fuzzy logic priority is proposed for opportunistic array radar(OAR). In this scheme,the total beam illuminating time is minimized by effective time resource allocation so that the desired tracking performance is achieved. Meanwhile, owing to the randomness of radar cross section(RCS), the CCP is used to balance tracking accuracy and time resource conditioned on the specified confidence level. The adaptive fuzzy logic prioritization, imitating the human decision-making process for ranking radar targets, can realize the full potential of radar. The Bayesian Crame ′r-Rao lower bound(BCRLB) provides us with a low bound of localization estimation root-mean-square error(RMSE), and equally important, it can be calculated predictively. Consequently, it is employed as an optimization criterion for the time resource allocation scheme. The stochastic simulation is integrated into the genetic algorithm(GA) to compose a hybrid intelligent optimization algorithm to solve the CCP optimization problem. The simulation results show that the time resource is saved strikingly and the radar performance is also improved.展开更多
文摘D-SOAR PLUS G 40000 W特高功率高速光纤激光切割机,主要针对高端客户精心配置,整机由瑞士百超集团技术团队领衔设计,主要零部件采用原装进口品牌,具有切割精度高、速度更快、操作更简单、使用成本更低和切割材料更广泛等特点,为客户提供了稳定的激光切割性能,减少了板材浪费,提高了生产能力。
基金supported by the National Natural Science Foundation of China(6127132761671241)
文摘For coping with the multiple target tracking in the presence of complex time-varying environments and unknown target information, a time resource management scheme based on chance-constraint programming(CCP) employing fuzzy logic priority is proposed for opportunistic array radar(OAR). In this scheme,the total beam illuminating time is minimized by effective time resource allocation so that the desired tracking performance is achieved. Meanwhile, owing to the randomness of radar cross section(RCS), the CCP is used to balance tracking accuracy and time resource conditioned on the specified confidence level. The adaptive fuzzy logic prioritization, imitating the human decision-making process for ranking radar targets, can realize the full potential of radar. The Bayesian Crame ′r-Rao lower bound(BCRLB) provides us with a low bound of localization estimation root-mean-square error(RMSE), and equally important, it can be calculated predictively. Consequently, it is employed as an optimization criterion for the time resource allocation scheme. The stochastic simulation is integrated into the genetic algorithm(GA) to compose a hybrid intelligent optimization algorithm to solve the CCP optimization problem. The simulation results show that the time resource is saved strikingly and the radar performance is also improved.