似然区间估计在武器精度分析中的应用

本文着重介绍了Kalbfleisch的似然区间估计方法,并结合到武器精度分析中几个重要参数的评估问题,与常用的一些区间估计进行了讨论和比较,证明了某军标提供的最精确无偏区间也是一种似然区间。最后以某型号导弹为例,说明在相同的置信水平条件下,似然区间更直观,区间更短,更具有使用价值。     

高频通信最大可用频率的自适应预报

引入Volterra级数自适应混沌预报方法, 实现了高频通信最大可用频率的自适应预报. 基于青岛至新乡2007年3月和2012年3月最大可用频率观测数据, 通过不同太阳活动期单步预报、不同步长短期预报和不同训练样本长度预报结果的统计, 分析验证了方法的精确性、适应性和有效性. 分析结果表明, 采用Volterra级数自适应混沌预报方法进行超短期预测可以取得较好的预报结果, 适用于不同太阳活动期; 预测步长不大于1/12周期时, 预报均方根误差均小于0.79MHz, 与基于最大Lyapunov指数预报方法的结果对比表明, 该方法在观测数据少和信道时变特性强等情形下仍具有较高精度且应用简便. 其为高频频率预报技术的深入研究提供了基础.      

Oblique shock train motion based on schlieren image processing

In this paper, shock train motion in a Mach number 2.7 duct is studied experimentally, and large numbers of schlieren images are obtained by a high-speed camera. An image processing method based on Maximum Correlation Detection (MCD) is proposed to detect shock train motion from the schlieren images, based on which the key structures, e.g., separation positions and separation shock angles on the top and bottom walls, can be analysed in detail. The oscillations of the shock train are generated by rhombus and ellipse shafts at various excitation frequencies. According to the analysis of MCD results, the distributions of the frequency components of shock train oscillation generated by the two shafts are distinctly different, in which the motion generated by the ellipse shaft is much smoother; shock train motion is mainly characterized by the oscillation of separation position while the separation shock strength is not so sensitive to downstream disturbance; there is a hysteresis loop relation between the downstream pressure and separation position.     

Topology optimization of turbine disk considering maximum stress prediction and constraints

For the stress-constrained topology optimization of a turbine disk under centrifugal loads, the jagged boundaries of the mesh and the gray densities on the solid/void interfaces could make the calculated stress field inconsistent with the actual value. It may result in overestimating the maximum stress and thus affect the effectiveness of stress constraints. This paper proposes a new method for predicting the maximum stress to overcome the difficulty. In the process, a predicted density is newly defined to obtain stable boundaries with thin layers of gray elements, a transition factor is innovatively proposed to evaluate the effects of intermediate-density elements, two different stiffness penalty schemes are flexibly used to calculate the elastic modulus of elements, and a linear stress penalty is further adopted to relax the stress field of the structure. The proposed approach for predicting the maximum stress value is verified by the analysis of a structure with smooth boundaries and the topology optimization of a turbine disk. An updating scheme of the stress constraint in the topology optimization is also developed using the predicted maximum stress. Some key ingredients affecting the optimization results are discussed in detail. The results prove the effectiveness and efficacy of the proposed maximum stress prediction and developed stress constraint methods.     

Improving multi-target cooperative tracking guidance for UAV swarms using multi-agent reinforcement learning

Multi-Target Tracking Guidance(MTTG) in unknown environments has great potential values in applications for Unmanned Aerial Vehicle(UAV) swarms. Although Multi-Agent Deep Reinforcement Learning(MADRL) is a promising technique for learning cooperation, most of the existing methods cannot scale well to decentralized UAV swarms due to their computational complexity or global information requirement. This paper proposes a decentralized MADRL method using the maximum reciprocal reward to learn cooper...     

SINS/GNSS integrated navigation system based on maximum versoria filter

In the missile-borne Strapdown Inertial Navigation System/Global Navigation Satellite System (SINS/GNSS) integrated navigation system, due to the factors such as the high dynamics, the signal blocking by obstacles, the signal intefereces, etc., there always exist pulse interferences or measurement information interruptions in the satellite receiver, which make nonstationary measurement process. The traditional Kalman Filter (KF) can tackle the state estimation problem under Gaussian white noise, but its performance will be significantly reduced under non-Gaussian noises. In order to deal with the non-Gaussian conditions in the actual missile-borne SINS/GNSS integrated navigation systems, a Maximum Versoria Criterion Extended Kalman Filter (MVC-EKF) algorithm is proposed based on the MVC and the idea of M-estimation, which assigns a smaller weight to the anomalous measurements so as to suppress the influence of anomalous measurements on the state estimation while maintaining a relatively low calculation cost. Finally, the integrated navigation simulation experiments prove the effectiveness and robustness of the proposed algorithm.