Aiming at some weapon systems with shooting domain,the stochastic passage characteristics of the barrel were studied.On the basis of the exact definition of the stochastic passage characteristics,its opportunity-await...Aiming at some weapon systems with shooting domain,the stochastic passage characteristics of the barrel were studied.On the basis of the exact definition of the stochastic passage characteristics,its opportunity-awaiting time,residence time and stochastic passage period were given by using the transition probability matrix,and they all obeyed the geometry distributions.Their means and variances were also derived,and the relations between the time indexes and the structure and parameters of weapon control system were established.Finally,the creditability of the conclusions was verified by the test data of weapon system in proving ground.展开更多
In some object tracking systems, the moving object future position is an area （i.e., target area）. It is a successful estimation strategy if the predicted points fall in the target area. If the object makes a sudden...In some object tracking systems, the moving object future position is an area （i.e., target area）. It is a successful estimation strategy if the predicted points fall in the target area. If the object makes a sudden maneuvering, the prediction may get out of the target area easily which may make the tracking system lose the object. The aim is to investigate the admissible maximum object maneuvering intensity, which is characterized as model noise variance, for such kind of tracking system. Firstly, the concept of stochastic passage characteristics over the boundary of target area and their relationship with prediction error variance are described. Secondly, the consistency among the indices of regional pole, prediction error variance and stochastic passage characteristics is analyzed. Thirdly, the multi-indices constraints are characterized by a set of bi-linear matrix inequalities （BMIs）. Then, the admissible maximum model noise variance and the satisfactory estimation strategy are presented by iteratively solving linear matrix inequalities （LMIs） to approximate BMIs. Finally, a numerical example is proposed to demonstrate the obtained resuits.展开更多
基金Sponsored by National Defense Fundation of China(9140C300602080C30)NUST Research Fundation of China(2010ZYTS050)
文摘Aiming at some weapon systems with shooting domain,the stochastic passage characteristics of the barrel were studied.On the basis of the exact definition of the stochastic passage characteristics,its opportunity-awaiting time,residence time and stochastic passage period were given by using the transition probability matrix,and they all obeyed the geometry distributions.Their means and variances were also derived,and the relations between the time indexes and the structure and parameters of weapon control system were established.Finally,the creditability of the conclusions was verified by the test data of weapon system in proving ground.
基金supported by the Science and Technology Development Fund of Nanjing University of Science and Technology(NUST)(XKF09020)NUST Research Fund(2010GJPY067,2010ZYTS050)the National Natural Science Foundation of China(60804019)
文摘In some object tracking systems, the moving object future position is an area （i.e., target area）. It is a successful estimation strategy if the predicted points fall in the target area. If the object makes a sudden maneuvering, the prediction may get out of the target area easily which may make the tracking system lose the object. The aim is to investigate the admissible maximum object maneuvering intensity, which is characterized as model noise variance, for such kind of tracking system. Firstly, the concept of stochastic passage characteristics over the boundary of target area and their relationship with prediction error variance are described. Secondly, the consistency among the indices of regional pole, prediction error variance and stochastic passage characteristics is analyzed. Thirdly, the multi-indices constraints are characterized by a set of bi-linear matrix inequalities （BMIs）. Then, the admissible maximum model noise variance and the satisfactory estimation strategy are presented by iteratively solving linear matrix inequalities （LMIs） to approximate BMIs. Finally, a numerical example is proposed to demonstrate the obtained resuits.
