基于双基阵的高炮弹丸炸点被动声定位研究

被动声定位技术在许多领域中有着广泛的应用,但定位精度低一直是影响其工程应用的关键问题之一。在研究单基阵被动声定位技术的基础上,提出了基于双基阵的被动声定位基本原理和方法,并对高炮弹丸炸点的被动声定位进行了仿真实验。仿真结果表明,采用双基阵对高炮弹丸炸点进行被动声定位,其精度有较大提高,克服了单基阵定位精度低的不足。此原理和方法同样适用于对其它三维空中目标进行被动声定位。     

基于冲量法实现航天器编队重构控制仿真的研究

针对航天器编队重构的可视性不强,提出一种冲量法实现航天器编队重构的视景仿真技术。双脉冲机动是指航天器对空间目标的近轨道转移时,所需要的两次冲量机动。应用航天器之间相对运动原理,以空间目标轨道六要素为目标函数,通过调整航天器轨道参数对空间目标进行编队重构,有摆动绕飞转移至摆动式悬挂绕飞,进而得出了航天器转移摆动式悬挂绕飞编队到所需冲量基本关系,从而实现航天器对空间目标进行编队重构控制。     

双壳体潜艇磁场变化的实验研究与特性分析

双壳体潜艇的磁化特征与单壳体潜艇有较大区别,为了将其磁化特性分析清楚,建立了双层圆柱形铁壳桶的简易潜艇模型,并将其放置于地球磁场环境中,利用通电线圈产生的强大磁场对潜艇模型进行局部磁化;然后,以潜艇垂向磁场变化量作为分析对象,并结合舰船磁场规律、磁滞特性、退磁场等理论,对双壳体潜艇的磁场变化规律进行了定性分析。研究结果表明:双壳体潜艇的外壳磁化规律近似于单壳体潜艇,而由于外壳屏蔽地球磁场,内壳几乎只受到线圈磁化影响。该结论可以为舰船消磁作业等提供理论依据。     

Autonomous maneuver decision-making for a UCAV in short-range aerial combat based on an MS-DDQN algorithm

To solve the problem of realizing autonomous aerial combat decision-making for unmanned combat aerial vehicles (UCAVs) rapidly and accurately in an uncertain environment, this paper proposes a decision-making method based on an improved deep reinforcement learning (DRL) algorithm: the multi-step double deep Q-network (MS-DDQN) algorithm. First, a six-degree-of-freedom UCAV model based on an aircraft control system is established on a simulation platform, and the situation assessment functions of the UCAV and its target are established by considering their angles, altitudes, environments, missile attack performances, and UCAV performance. By controlling the flight path angle, roll angle, and flight velocity, 27 common basic actions are designed. On this basis, aiming to overcome the defects of traditional DRL in terms of training speed and convergence speed, the improved MS-DDQN method is introduced to incorporate the final return value into the previous steps. Finally, the pre-training learning model is used as the starting point for the second learning model to simulate the UCAV aerial combat decision-making process based on the basic training method, which helps to shorten the training time and improve the learning efficiency. The improved DRL algorithm significantly accelerates the training speed and estimates the target value more accurately during training, and it can be applied to aerial combat decision-making.     

Nb掺杂对双钙钛矿化合物Sr2FeMoO6电阻特性的影响

系统地研究了双钙钛矿结构氧化物Sr2FeMo1-xNbxO6中Mo位的Nb替代效应,发现Nb替代Mo可强烈抑制Sr2FeMoO6的金属导电性,并大大提高掺杂样品的电阻值和庞磁电阻特性,在5K下,Sr2FeMo0.6Nb0.4O6的庞磁电阻分别达到23%(1T)和31%(3T),在室温下,Sr2FeMo0.75Nb0.25O6的磁电阻分别达到4%(1T)和6%(3T).