The ever-changing battlefield environment requires the use of robust and adaptive technologies integrated into a reliable platform. Unmanned combat aerial vehicles(UCAVs) aim to integrate such advanced technologies wh...The ever-changing battlefield environment requires the use of robust and adaptive technologies integrated into a reliable platform. Unmanned combat aerial vehicles(UCAVs) aim to integrate such advanced technologies while increasing the tactical capabilities of combat aircraft. As a research object, common UCAV uses the neural network fitting strategy to obtain values of attack areas. However, this simple strategy cannot cope with complex environmental changes and autonomously optimize decision-making problems. To solve the problem, this paper proposes a new deep deterministic policy gradient(DDPG) strategy based on deep reinforcement learning for the attack area fitting of UCAVs in the future battlefield. Simulation results show that the autonomy and environmental adaptability of UCAVs in the future battlefield will be improved based on the new DDPG algorithm and the training process converges quickly. We can obtain the optimal values of attack areas in real time during the whole flight with the well-trained deep network.展开更多
This paper provides a calculating method which can be used in calculation of the kill probability attack area for every AAM. At first, attack area of AAM and kill probability of every characteristic point are obtained...This paper provides a calculating method which can be used in calculation of the kill probability attack area for every AAM. At first, attack area of AAM and kill probability of every characteristic point are obtained by combining trajectory calculation with kill probability calculation. Then, coordinates of a fire point relative to standard kill probability value in terms of standardization method are found. At last, equivalent kill probability curve equations are formulated by means of curve fitting method.展开更多
A new method called local accurate search is put forward to calculate the allowable area for air-to-surface missiles based on the conventional methods. Comparing with traditional methods, the local accurate search met...A new method called local accurate search is put forward to calculate the allowable area for air-to-surface missiles based on the conventional methods. Comparing with traditional methods, the local accurate search method can search the area online and reduce the time of search with the required precision. Combining the traditional flight range table with a model calculation method, the new method employs the local search to fred an accurate result, which will meet the fast-calculation requirements for attacking moving targets. In this way, the missiles are adapted for the complex warfare situation.展开更多
基金supported by the Key Laboratory of Defense Science and Technology Foundation of Luoyang Electro-optical Equipment Research Institute(6142504200108)。
文摘The ever-changing battlefield environment requires the use of robust and adaptive technologies integrated into a reliable platform. Unmanned combat aerial vehicles(UCAVs) aim to integrate such advanced technologies while increasing the tactical capabilities of combat aircraft. As a research object, common UCAV uses the neural network fitting strategy to obtain values of attack areas. However, this simple strategy cannot cope with complex environmental changes and autonomously optimize decision-making problems. To solve the problem, this paper proposes a new deep deterministic policy gradient(DDPG) strategy based on deep reinforcement learning for the attack area fitting of UCAVs in the future battlefield. Simulation results show that the autonomy and environmental adaptability of UCAVs in the future battlefield will be improved based on the new DDPG algorithm and the training process converges quickly. We can obtain the optimal values of attack areas in real time during the whole flight with the well-trained deep network.
文摘This paper provides a calculating method which can be used in calculation of the kill probability attack area for every AAM. At first, attack area of AAM and kill probability of every characteristic point are obtained by combining trajectory calculation with kill probability calculation. Then, coordinates of a fire point relative to standard kill probability value in terms of standardization method are found. At last, equivalent kill probability curve equations are formulated by means of curve fitting method.
文摘A new method called local accurate search is put forward to calculate the allowable area for air-to-surface missiles based on the conventional methods. Comparing with traditional methods, the local accurate search method can search the area online and reduce the time of search with the required precision. Combining the traditional flight range table with a model calculation method, the new method employs the local search to fred an accurate result, which will meet the fast-calculation requirements for attacking moving targets. In this way, the missiles are adapted for the complex warfare situation.
