为解决在雷达组网中高斯混合概率假设密度滤波(Gaussian mixture probability hypothesis density filter,GMPHDF)难以跟踪非线性系统目标的问题,构建一种高斯无迹混合概率假设密度滤波(Gaussian unscented mixture probability hypothe...为解决在雷达组网中高斯混合概率假设密度滤波(Gaussian mixture probability hypothesis density filter,GMPHDF)难以跟踪非线性系统目标的问题,构建一种高斯无迹混合概率假设密度滤波(Gaussian unscented mixture probability hypothesis density filter,GUMPHDF)方法。将新生、衍生和继续存在目标的高斯元素分别用无迹滤波(unscented filter,UF)进行预测与更新,得到各目标的高斯无迹混合元素,再进入裁剪合并与状态提取程序。仿真结果表明:将该方法应用于炮兵雷达组网跟踪强杂波环境下,能跟踪到探测区域所有目标,精度较高,符合工程实践要求。展开更多
Homing trajectory planning is a core task of autonomous homing of parafoil system.This work analyzes and establishes a simplified kinematic mathematical model,and regards the homing trajectory planning problem as a ki...Homing trajectory planning is a core task of autonomous homing of parafoil system.This work analyzes and establishes a simplified kinematic mathematical model,and regards the homing trajectory planning problem as a kind of multi-objective optimization problem.Being different from traditional ways of transforming the multi-objective optimization into a single objective optimization by weighting factors,this work applies an improved non-dominated sorting genetic algorithm Ⅱ(NSGA Ⅱ) to solve it directly by means of optimizing multi-objective functions simultaneously.In the improved NSGA Ⅱ,the chaos initialization and a crowding distance based population trimming method were introduced to overcome the prematurity of population,the penalty function was used in handling constraints,and the optimal solution was selected according to the method of fuzzy set theory.Simulation results of three different schemes designed according to various practical engineering requirements show that the improved NSGA Ⅱ can effectively obtain the Pareto optimal solution set under different weighting with outstanding convergence and stability,and provide a new train of thoughts to design homing trajectory of parafoil system.展开更多
This paper treats multi-objective problem for manufacturing process design. A purpose of the process design is to decide combinations of work elements assigned to different work centers. Multiple work elements are ord...This paper treats multi-objective problem for manufacturing process design. A purpose of the process design is to decide combinations of work elements assigned to different work centers. Multiple work elements are ordinarily assigned to each center. Here, infeasible solutions are easily generated by precedence relationship of work elements in process design. The number of infeasible solutions generated is ordinarily larger than that of feasible solutions generated in the process. Therefore, feasible and infeasible solutions are located in any neighborhood in solution space. It is difficult to seek high quality Pareto solutions in this problem by using conventional multi-objective evolutional algorithms. We consider that the problem includes difficulty to seek high quality solutions by the following characteristics： （1） Since infeasible solutions are resemble to good feasible solutions, many infeasible solutions which have good values of objective functions are easily sought in the search process, （2） Infeasible solutions are useful to select new variable conditions generating good feasible solutions in search process. In this study, a multi-objective genetic algorithm including local search is proposed using these characteristics. Maximum value of average operation times and maximum value of dispersion of operation time in all work centers are used as objective functions to promote productivity. The optimal weighted coefficient is introduced to control the ratio of feasible solutions to all solutions selected in crossover and selection process in the algorithm. This paper shows the effectiveness of the proposed algorithm on simple model.展开更多
This paper presents a novel coverage-based cooperative target acquisition algorithm for hypersonic interceptions. Firstly, the difficulties in the hypersonic trajectory prediction are introduced which invalidate the c...This paper presents a novel coverage-based cooperative target acquisition algorithm for hypersonic interceptions. Firstly, the difficulties in the hypersonic trajectory prediction are introduced which invalidate the conventionally used predicted impact point based mid-course guidance and seeker acquisition. Secondly, in order to optimally estimate and predict the target trajectory information, the interacting multiple model(IMM) algorithm is used with the constant velocity(CV) model, the constant acceleration(CA) model and the Singer model serving as the model set. The target states are described with the probability density function(PDF) based on the IMM prediction. Thirdly, the interceptor seeker target acquisition model is established which considers the blur edge region of the field of view. The cooperative target acquisition algorithm is designed by maximizing the interceptor seekers cooperative coverage of the target high probability region(HPR). Finally, digital simulations prove the effectiveness of the proposed method and reveal that the real challenge in the hypersonic target acquisition is the poor trajectory prediction accuracy which may further result to the unsteadiness of the interceptor trajectories.展开更多
文摘为解决在雷达组网中高斯混合概率假设密度滤波(Gaussian mixture probability hypothesis density filter,GMPHDF)难以跟踪非线性系统目标的问题,构建一种高斯无迹混合概率假设密度滤波(Gaussian unscented mixture probability hypothesis density filter,GUMPHDF)方法。将新生、衍生和继续存在目标的高斯元素分别用无迹滤波(unscented filter,UF)进行预测与更新,得到各目标的高斯无迹混合元素,再进入裁剪合并与状态提取程序。仿真结果表明:将该方法应用于炮兵雷达组网跟踪强杂波环境下,能跟踪到探测区域所有目标,精度较高,符合工程实践要求。
基金Project(61273138)supported by the National Natural Science Foundation of ChinaProject(14JCZDJC39300)supported by the Key Fund of Tianjin,China
文摘Homing trajectory planning is a core task of autonomous homing of parafoil system.This work analyzes and establishes a simplified kinematic mathematical model,and regards the homing trajectory planning problem as a kind of multi-objective optimization problem.Being different from traditional ways of transforming the multi-objective optimization into a single objective optimization by weighting factors,this work applies an improved non-dominated sorting genetic algorithm Ⅱ(NSGA Ⅱ) to solve it directly by means of optimizing multi-objective functions simultaneously.In the improved NSGA Ⅱ,the chaos initialization and a crowding distance based population trimming method were introduced to overcome the prematurity of population,the penalty function was used in handling constraints,and the optimal solution was selected according to the method of fuzzy set theory.Simulation results of three different schemes designed according to various practical engineering requirements show that the improved NSGA Ⅱ can effectively obtain the Pareto optimal solution set under different weighting with outstanding convergence and stability,and provide a new train of thoughts to design homing trajectory of parafoil system.
文摘This paper treats multi-objective problem for manufacturing process design. A purpose of the process design is to decide combinations of work elements assigned to different work centers. Multiple work elements are ordinarily assigned to each center. Here, infeasible solutions are easily generated by precedence relationship of work elements in process design. The number of infeasible solutions generated is ordinarily larger than that of feasible solutions generated in the process. Therefore, feasible and infeasible solutions are located in any neighborhood in solution space. It is difficult to seek high quality Pareto solutions in this problem by using conventional multi-objective evolutional algorithms. We consider that the problem includes difficulty to seek high quality solutions by the following characteristics： （1） Since infeasible solutions are resemble to good feasible solutions, many infeasible solutions which have good values of objective functions are easily sought in the search process, （2） Infeasible solutions are useful to select new variable conditions generating good feasible solutions in search process. In this study, a multi-objective genetic algorithm including local search is proposed using these characteristics. Maximum value of average operation times and maximum value of dispersion of operation time in all work centers are used as objective functions to promote productivity. The optimal weighted coefficient is introduced to control the ratio of feasible solutions to all solutions selected in crossover and selection process in the algorithm. This paper shows the effectiveness of the proposed algorithm on simple model.
基金supported by the National Natural Science Foundation of China(Grant Nos.61573374,61503408,61703421,and 61773398)
文摘This paper presents a novel coverage-based cooperative target acquisition algorithm for hypersonic interceptions. Firstly, the difficulties in the hypersonic trajectory prediction are introduced which invalidate the conventionally used predicted impact point based mid-course guidance and seeker acquisition. Secondly, in order to optimally estimate and predict the target trajectory information, the interacting multiple model(IMM) algorithm is used with the constant velocity(CV) model, the constant acceleration(CA) model and the Singer model serving as the model set. The target states are described with the probability density function(PDF) based on the IMM prediction. Thirdly, the interceptor seeker target acquisition model is established which considers the blur edge region of the field of view. The cooperative target acquisition algorithm is designed by maximizing the interceptor seekers cooperative coverage of the target high probability region(HPR). Finally, digital simulations prove the effectiveness of the proposed method and reveal that the real challenge in the hypersonic target acquisition is the poor trajectory prediction accuracy which may further result to the unsteadiness of the interceptor trajectories.
